Issuu on Google+


The world by income

Low ($1,025 or less)

Lower middle ($1,026–$4,035)

Upper middle ($4,036–$12,475)

High ($12,476 or more)

No data

Classified according to World Bank estimates of 2011 GNI per capita

Greenland (Den)

Iceland

Norway

Faeroe Islands (Den)

Sweden

Finland

Russian Federation

The Netherlands

Estonia Denmark Russian Latvia Fed. Lithuania United Belarus Germany Poland Kingdom Belgium Ukraine Moldova Romania France Italy

Isle of Man (UK)

Canada

Ireland Channel Islands (UK)

Luxembourg Liechtenstein Switzerland Andorra United States

Bulgaria

Portugal

Spain Monaco Tunisia Algeria

Cayman Is.(UK)

Mexico

Costa Rica

Jordan

Libya

Arab Rep. of Egypt

Cape Verde

Mali

Niger

Chad

Senegal

The Gambia Guinea-Bissau R.B. de Venezuela

Guyana Suriname

Burkina Faso

Guinea

Sierra Leone Liberia

French Guiana (Fr)

Benin

Côte Ghana d’Ivoire

Nigeria Cameroon

Central African Republic

Gabon

Congo

Malawi

Zambia Bolivia Zimbabwe

Tonga

Namibia Paraguay Germany

St. Martin (Fr) St. Maarten (Neth)

Antigua and Barbuda St. Kitts and Nevis

Curaçao (Neth)

St. Vincent and the Grenadines

Dominica St. Lucia Barbados Grenada

R.B. de Venezuela

Argentina

Trinidad and Tobago

Poland

Czech Republic Ukraine Slovak Republic Austria

Guadeloupe (Fr)

Martinique (Fr) Aruba (Neth)

Chile

Uruguay

N. Mariana Islands (US) Guam (US)

Philippines

Federated States of Micronesia

Brunei Darussalam Malaysia

Marshall Islands

Palau

Maldives Nauru

Singapore

Botswana

Comoros

Solomon Islands

Papua New Guinea

Indonesia

Mayotte (Fr)

Madagascar

Tuvalu

Vanuatu

Fiji

Mauritius Réunion (Fr)

Australia

New Caledonia (Fr)

Lesotho

New Zealand

Hungary

Slovenia Croatia

Romania

Bosnia and Herzegovina San Marino Italy Montenegro Vatican City

South Africa

Kiribati

Seychelles

Mozambique

Swaziland

U.S. Virgin Islands (US)

Sri Lanka Somalia

Angola

Puerto Rico (US)

Lao P.D.R.

Timor-Leste

French Polynesia (Fr) American Samoa (US)

Myanmar

Vietnam Cambodia

Brazil

Peru

Bangladesh India

Thailand

Kenya

Rwanda Dem.Rep.of Burundi Congo Tanzania

Japan

Bhutan

Nepal

Rep. of Yemen

Ethiopia

South Sudan Uganda

Kiribati

Dominican Republic

Pakistan

United Arab Emirates Oman

Rep.of Korea

China

Afghanistan

Djibouti

Togo Equatorial Guinea São Tomé and Príncipe

Ecuador

Eritrea

Dem.People’s Rep.of Korea

Tajikistan

Bahrain Qatar Saudi Arabia

Sudan

Turkmenistan

Islamic Rep. of Iran Kuwait

Iraq

Mongolia Kyrgyz Rep.

Uzbekistan

Azerbaijan

Mauritania

Colombia

Fiji

West Bank and Gaza

Western Sahara

Haiti

Panama

Samoa

Syrian Arab Rep.

Turks and Caicos Is. (UK)

Cuba Belize Jamaica Guatemala Honduras El Salvador Nicaragua

Georgia Armenia

Cyprus Lebanon Israel

Malta

Morocco

The Bahamas

Turkey

Greece

Gibraltar (UK)

Bermuda (UK)

Kazakhstan

Serbia

Kosovo Bulgaria FYR Macedonia Albania Greece

Antarctica

IBRD 39817 MARCH 2013

Designed, edited, and produced by Communications Development Incorporated, Washington, D.C., with Peter Grundy Art & Design, London


2013

World Development Indicators


© 2013 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW, Washington DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org Some rights reserved 1 2 3 4 16 15 14 13 This work is a product of the staff of The World Bank with external contributions. Note that The World Bank does not necessarily own each component of the content included in the work. The World Bank therefore does not warrant that the use of the content contained in the work will not infringe on the rights of third parties. The risk of claims resulting from such infringement rests solely with you. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Nothing herein shall constitute or be considered to be a limitation upon or waiver of the privileges and immunities of The World Bank, all of which are specifically reserved. Rights and Permissions

This work is available under the Creative Commons Attribution 3.0 Unported license (CC BY 3.0) http://creativecommons.org/licenses/by/3.0. Under the Creative Commons Attribution license, you are free to copy, distribute, transmit, and adapt this work, including for commercial purposes, under the following conditions: Attribution—Please cite the work as follows: World Bank. 2013. World Development Indicators 2013. Washington, DC: World Bank. doi: 10.1596/978-0-8213-9824-1. License: Creative Commons Attribution CC BY 3.0 Translations—If you create a translation of this work, please add the following disclaimer along with the attribution: This translation was not created by The World Bank and should not be considered an official World Bank translation. The World Bank shall not be liable for any content or error in this translation. All queries on rights and licenses should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2625; e-mail: pubrights@ worldbank.org. ISBN (paper): 978-0-8213-9824-1 ISBN (electronic): 978-0-8213-9825-8 DOI: 10.1596/978-0-8213-9824-1 Cover photo: Arne Hoel/World Bank; Cover design: Communications Development Incorporated. Other photos: page xviii, Arne Hoel/World Bank; page 34, Kim Eun Yeul/World Bank; page 50, Curt Carnemark/World Bank; page 64, Gerardo Pesantez/ World Bank; page 78, Maria Fleischmann/ World Bank; page 92, Curt Carnemark/World Bank.


Preface Welcome to World Development Indicators 2013, the World Bank’s premier compilation of relevant, highquality, and internationally comparable statistics about global development. The first edition of World Development Indicators in 1997 included this forecast: “The global economy is undergoing an information revolution that will be as significant in effect as the industrial revolution of the nineteenth century.” At that time the number of mobile phones worldwide was estimated to be less than 2  per 100  people, with eight times as many telephone mainlines. World Development Indicators has tracked the revolution: this edition reports that mobile phone subscriptions in 2011 grew to 85 per 100 people—a more than fortyfold increase. This is just one example of how people were communicating and acquiring knowledge and how information was changing. But in addition to measuring the change, World Development Indicators has felt it directly. Use of the online database and the tools that access it—particularly the Open Data website (http://data.worldbank.org), the web-based DataBank query application (http://databank.worldbank.org), and applications for mobile devices—has increased dramatically. And so we have refined and improved the presentation of this 17th edition. Our aim is to find the best way to put data in the hands of policymakers, development specialists, students, and the public, so that they may use the data to reduce poverty and solve the world’s most pressing development challenges. The biggest change is that the data tables previously published in the book are now available online (http://wdi.worldbank.org/tables). This has many advantages: The tables will reflect the latest

additions and revisions to the data. They will be available to a far greater audience. And they will be free for everyone. World Development Indicators 2013 is organized around six themes—world view, people, environment, economy, states and markets, and global links. Each section includes an introduction, a set of six stories highlighting regional trends, a table of the most relevant and popular indicators, and an index to the full set of tables and indicators available online. World view also reviews progress toward the Millennium Development Goals. Other companion products include The Little Data Book 2013, which provides an at-a-glance view of indicators for each economy, and a new version of the DataFinder mobile application, available in Chinese, English, French, and Spanish and designed to reflect the structure and tables of World Development Indicators 2013, for both tablet and handheld devices and for all major mobile platforms (http://data.worldbank .org/apps). World Development Indicators is the result of a collaborative effort of many partners: the United Nations family, the International Monetary Fund, the International Telecommunication Union, the Organisation for Economic Co-operation and Development, the statistical offices of more than 200 economies, and countless others. I extend my gratitude to them all—and especially to government statisticians around the world. Without their hard work, professionalism, and dedication, measuring and monitoring trends in global development would not be possible. We hope you will find the new World Development Indicators a useful resource, and we welcome any suggestions to improve it at data@worldbank.org. Shaida Badiee Director Development Economics Data Group

Economy

States and markets

Global links

Back

World Development Indicators 2013 iii


Acknowledgments This book was prepared by a team led by Soong Sup Lee under the management of Neil Fantom and comprising Azita Amjadi, Liu Cui, Federico Escaler, Mahyar Eshragh-Tabary, Juan Feng, Masako Hiraga, Wendy Ven-dee Huang, Bala Bhaskar Naidu Kalimili, Buyant Khaltarkhuu, Elysee Kiti, Alison Kwong, Ibrahim Levent, Hiroko Maeda, Johan Mistiaen, Vanessa Moreira da Silva, Maurice Nsabimana, Beatriz Prieto-Oramas, William Prince, Evis Rucaj, Rubena Sukaj, Emi Suzuki, Eric Swanson, Jomo Tariku, Rasiel Victor Vellos, and Olga Victorovna Vybornaia, working closely with other teams in the Development Economics Vice Presidency’s Development Data Group. World Development Indicators electronic products were prepared by a team led by Reza Farivari and comprising Ying Chi, Jean‑Pierre Djomalieu, Ramgopal Erabelly, Shelley Fu, Gytis Kanchas, Siddhesh Kaushik, Ugendran Machakkalai, Nacer Megherbi, Shanmugam Natarajan, Parastoo Oloumi, Manish Rathore, Ashish Shah, Atsushi Shimo, Malarvizhi Veerappan, and Vera Wen. All work was carried out under the direction of Shaida Badiee. Valuable advice was provided by

iv 

World Development Indicators 2013

Front

?

User guide

Tito Cordella, Doerte Doemeland, Zia M. Qureshi, and David Rosenblatt. The choice of indicators and text content was shaped through close consultation with and substantial contributions from staff in the World Bank’s four thematic networks—Sustainable Development, Human Development, Poverty Reduction and Economic Management, and Financial and Private Sector Development—and staff of the International Finance Corporation and the Multilateral Investment Guarantee Agency. Most important, the team received substantial help, guidance, and data from external partners. For individual acknowledgments of contributions to the book’s content, see Credits. For a listing of our key partners, see Partners. Communications Development Incorporated provided overall design direction, editing, and layout, led by Meta de Coquereaumont, Jack Harlow, Bruce Ross-Larson, and Christopher Trott. Elaine Wilson created the cover and graphics and typeset the book. Peter Grundy, of Peter Grundy Art & Design, and Diane Broadley, of Broadley Design, designed the report. Staff from The World Bank’s Office of the Publisher oversaw printing and dissemination of the book.

World view

People

Environment


Table of contents Prefaceiii Acknowledgmentsiv Partnersvi User guide

1. World

xii

view1

2. People35 3. Environment51

Introduction Goal 1 Eradicate extreme poverty Goal 2 Achieve universal primary education Goal 3 Promote gender equality and empower women Goal 4 Reduce child mortality Goal 5 Improve maternal health Goal 6 Combat HIV/AIDS, malaria, and other diseases Goal 7 Ensure environmental sustainability Goal 8 Develop a global partnership for development Targets and indicators for each goal World view indicators About the data Online tables and indicators Poverty indicators NEW! About the data

4. Economy65 5. States

and markets79

6. Global

links93

Primary data documentation

107

Statistical methods

118

Introduction Highlights Table of indicators About the data Online tables and indicators

Credits121

Economy

States and markets

Global links

Back

World Development Indicators 2013 v


Partners Defining, gathering, and disseminating international statistics is a collective effort of many people and organizations. The indicators presented in World Development Indicators are the fruit of decades of work at many levels, from the field workers who administer censuses and household surveys to the committees and working parties of the national and international statistical agencies that develop the nomenclature, classifications, and standards fundamental to an international statistical system. Nongovernmental organizations and the private sector have also made important contributions, both in gathering primary data and in organizing and publishing their results. And academic researchers have played a crucial role in developing statistical methods and carrying on a continuing dialogue about the quality and interpreta-

vi 

World Development Indicators 2013

Front

?

User guide

tion of statistical indicators. All these contributors have a strong belief that available, accurate data will improve the quality of public and private decisionmaking. The organizations listed here have made World Development Indicators possible by sharing their data and their expertise with us. More important, their collaboration contributes to the World Bank’s efforts, and to those of many others, to improve the quality of life of the world’s people. We acknowledge our debt and gratitude to all who have helped to build a base of comprehensive, quantitative information about the world and its people. For easy reference, web addresses are included for each listed organization. The addresses shown were active on March 1, 2013.

World view

People

Environment


International and government agencies Carbon Dioxide Information Analysis Center

International Diabetes Federation

http://cdiac.ornl.gov

www.idf.org

Centre for Research on the Epidemiology of Disasters

International Energy Agency

www.emdat.be

www.iea.org

Deutsche Gesellschaft fテシr Internationale Zusammenarbeit

International Labour Organization

www.giz.de

www.ilo.org

Food and Agriculture Organization

International Monetary Fund

www.fao.org

www.imf.org

Internal Displacement Monitoring Centre

International Telecommunication Union

www.internal-displacement.org/

www.itu.int

International Civil Aviation Organization

Joint United Programme on HIV/AIDS

www.icao.int

www.unaids.org

Economy

States and markets

Global links

Back

World Development Indicators 2013窶プii


Partners

viii 

National Science Foundation

United Nations Centre for Human Settlements, Global Urban Observatory

www.nsf.gov

www.unhabitat.org

The Office of U.S. Foreign Disaster Assistance

United Nations Children’s Fund

www.globalcorps.com/ofda.html

www.unicef.org

Organisation for Economic Co-operation and Development

United Nations Conference on Trade and Development

www.oecd.org

www.unctad.org

Stockholm International Peace Research Institute

United Nations Department of Economic and Social Affairs, Population Division

www.sipri.org

www.un.org/esa/population

Understanding Children’s Work

United Nations Department of Peacekeeping Operations

www.ucw-project.org

www.un.org/en/peacekeeping

United Nations

United Nations Educational, Scientific, and Cultural Organization, Institute for Statistics

www.un.org

www.uis.unesco.org

World Development Indicators 2013

Front

?

User guide

World view

People

Environment


United Nations Environment Programme

Upsalla Conflict Data Program

www.unep.org

www.pcr.uu.se/research/UCDP

United Nations Industrial Development Organization

World Bank

www.unido.org

http://data.worldbank.org

United Nations International Strategy for Disaster Reduction

World Health Organization

www.unisdr.org

www.who.int

United Nations Office on Drugs and Crime

World Intellectual Property Organization

www.unodc.org

www.wipo.int

United Nations Office of the High Commissioner for Refugees

World Tourism Organization

www.unhcr.org

www.unwto.org

United Nations Population Fund

World Trade Organization

www.unfpa.org

www.wto.org

Economy

States and markets

Global links

Back

World Development Indicators 2013 ix


Partners Private and nongovernmental organizations

x 

Center for International Earth Science Information Network

International Institute for Strategic Studies

www.ciesin.org

www.iiss.org

Containerisation International

International Road Federation

www.ci-online.co.uk

www.irfnet.org

DHL

Netcraft

www.dhl.com

http://news.netcraft.com

World Development Indicators 2013

Front

?

User guide

World view

People

Environment


PwC

World Economic Forum

www.pwc.com

www.weforum.org

Standard & Poor’s

World Resources Institute

www.standardandpoors.com

www.wri.org

World Conservation Monitoring Centre

www.unep-wcmc.org

Economy

States and markets

Global links

Back

World Development Indicators 2013 xi


User guide to tables World Development Indicators is the World Bank’s premier compilation of cross-country comparable data on development. The database contains more than 1,200 time series indicators for 214 economies and more than 30 country groups, with data for many indicators going back more than 50 years. The 2013 edition of World Development Indicators has been reconfigured to offer a more condensed presentation of the principal indicators, arranged in their traditional sections, along with regional and topical highlights.

3 Environment Deforestation

average annual % 2000–10

Afghanistan

 Economy

  States and markets

million metric tons

Per capita kilograms of oil equivalent

billion kilowatt hours

2010

2009

2010

2010

1,335

50

37

4.0

30

8,364

95

94

2.4

38

3.0

648

7.6

313

83

95

2.6

69

121.3

1,138

45.6

American Samoa

0.19

16.7

..

..

..

1.9

..

..

..

6.3

6.1

3,663

100

100

0.9

18

0.5

..

..

0.21

12.1

7,544

51

58

4.1

58

26.7

716

5.3

1.0

580

..

..

1.0

13

0.5

..

..

Argentina

0.81

5.3

6,771

..

..

1.0

57

174.7

1,847

125.3

Armenia

1.48

8.0

2,212

98

90

0.3

45

4.5

791

6.5

Aruba

0.00

0.0

..

100

..

0.8

..

2.3

..

..

0.37

12.5

22,039

100

100

1.3

13

400.2

5,653

241.5

–0.13

22.9

6,529

100

100

0.7

27

62.3

4,034

67.9

7.1

885

80

49.1

1,307

..

82

1.8

100

1.5

..

2.6

..

..

–3.55

0.7

3

..

..

4.9

44

24.2

7,754

13.2

Bangladesh

0.18

1.6

698

81

56

3.0

115

51.0

209

42.3

Barbados

0.00

0.1

292

100

100

1.4

35

1.6

..

0.00 0.00

1.0

58

27

World Development Indicators 2013

7.2

3,927

100

93

0.4

6

60.3

2,922

34.9

–0.16

13.2

1,089

100

100

1.2

21

103.6

5,586

93.8

0.67

20.6

44,868

98

90

3.0

12

0.4

..

..

13

4.2

0.2

Benin

48

4.9

413

0.00

5.1

..

..

..

0.7

..

0.5

..

Bhutan

–0.34

28.3

105,653

96

44

3.9

20

0.4

..

Bolivia

0.50

18.5

30,085

88

27

2.2

57

14.5

737

6.9

Bosnia and Herzegovina

0.00

0.6

9,461

99

95

0.9

21

30.1

1,703

17.1

Botswana

0.99

30.9

1,182

96

62

2.2

64

4.4

1,128

0.5 515.7

Burkina Faso

Front

?

User guide

1.04

23.3

1,132

75

98

79

.. ..

0.50

26.0

27,551

1.2

18

367.1

1,363

0.44

29.6

20,939

..

..

2.2

44

9.3

8,308

3.9

–1.53

8.9

2,858

100

100

–1.7

40

42.8

2,370

46.0

1.01

14.2

737

79

17

6.2

65

1.7

..

46

1.40

4.8

1,173

72

24

0.2

Cambodia

1.34

23.4

8,431

64

31

2.1

42

4.6

355

1.0

1.05

9.0

13,629

77

49

3.3

59

6.7

363

5.9

0.00

6.2

82,647

100

100

1.2

15

513.9

7,380

607.8 ..

Canada Cape Verde

599

88

61

0.3

..

0.00

1.5

..

96

96

..

0.5

..

0.13

17.7

31,425

67

34

2.6

35

0.2

..

0.66

9.4

1,301

51

13

3.0

83

0.4

..

..

..

0.5

..

..

..

0.8

..

..

..

..

Chile

–0.25

13.3

51,188

96

96

1.1

46

66.7

1,807

60.4

China

–1.57

16.0

2,093

91

64

3.0

59

7,687.1

1,807

4,208.3

37.0

1,951

38.3

Macao SAR, China

..

41.8

..

..

2.1 0.9

..

0.1

..

2.2

..

..

Chad

Hong Kong SAR, China

0.2

..

Central African Republic Channel Islands

–0.36

4.9

..

Burundi Cameroon

Cayman Islands

..

.. ..

..

..

..

..

..

1.5

..

..

Colombia

0.17

20.5

45,006

92

77

1.7

19

71.2

696

56.8

Comoros

9.34

..

1,592

95

36

2.9

30

0.1

..

..

Congo, Dem. Rep.

0.20

10.0

13,283

45

24

4.3

35

2.7

360

7.9

Congo, Rep.

0.07

9.7

53,626

71

18

3.0

57

1.9

363

0.6

Front

World Development Indicators 2013

Users guide

World view

People

Data presentation conventions • A blank means not applicable or, for an aggregate, not analytically meaningful. • A billion is 1,000 million. • A trillion is 1,000 billion. • Figures in orange italics refer to years or periods other than those specified or to growth rates calculated for less than the full period specified. • Data for years that are more than three years from the range shown are footnoted. • The cutoff date for data is February 1, 2013.

World view

..

–0.43

Belgium

Aggregate measures for income groups

xii 

18.7

Belarus

Bulgaria

The aggregate measures for regions cover only low- and middle-income economies. The country composition of regions is based on the World Bank’s analytical regions and may differ from common geographic usage. For regional classifications, see the map on the inside back cover and the list on the back cover flap. For further discussion of aggregation methods, see Statistical methods.

..

0.00 0.20

Brunei Darussalam

Aggregate measures for regions

..

Antigua and Barbuda

Brazil

Aggregate measures for income groups include the 214 economies listed in the tables, plus Taiwan, China, whenever data are available. To maintain consistency in the aggregate measures over time and between tables, missing data are imputed where possible.

..

Angola

Belize

46

1990–2011

0.4

Bermuda

The tables include all World Bank member countries (188), and all other economies with populations of more than 30,000 (214 total). Countries and economies are listed alphabetically (except for Hong Kong SAR, China, and Macao SAR, China, which appear after China). The term country, used interchangeably with economy, does not imply political independence but refers to any territory for which authorities report separate social or economic statistics. When available, aggregate measures for income and regional groups appear at the end of each table.

2010

8.4

Bahamas, The

Tables

% of total population

2010

Energy use Electricity production

weighted PM10 micrograms per cubic meter

6.2

Bahrain

  Global links

% of total population

average annual % growth

0.57

Azerbaijan

 Environment

2011

Access to Urban Particulate Carbon improved population matter dioxide sanitation concentration emissions facilities urban-population-

–0.10

Austria

 People

2011

Access to improved water source

Albania

Australia

  World view

Internal renewable freshwater

Algeria Andorra

0.00

Nationally protected areas

b Terrestrial and resources marine areas Per capita % of total territorial area cubic meters

People

Environment

Environment


Classification of economies For operational and analytical purposes the World Bank’s main criterion for classifying economies is gross national income (GNI) per capita (calculated using the World Bank Atlas method). Because GNI per capita changes over time, the country composition of income groups may change from one edition of World Development Indicators to the next. Once the classification is fixed for an edition, based on GNI per capita in the most recent year for which data are available (2011 in this edition), all historical data presented are based on the same country grouping. Low-income economies are those with a GNI per capita of $1,025 or less in 2011. Middle-income economies are those with a GNI per capita of more than $1,025 but less than $12,475. Lower middle-income and upper middleincome economies are separated at a GNI per capita of $4,036. High-income economies are those with a GNI per capita of $12,476 or more. The 17 participating member countries of the euro area are presented as a subgroup under high income economies.

Environment 3 Deforestation

average annual % 2000–10

Nationally protected areas

Internal renewable freshwater b Terrestrial and resources marine areas Per capita % of total territorial area cubic meters 2011

2011

Access to improved water source

Access to Urban Particulate Carbon improved population matter dioxide sanitation concentration emissions facilities urban-population-

% of total population

% of total population

average annual % growth

2010

2010

1990–2011

Energy use Electricity production

weighted PM10 micrograms per cubic meter

million metric tons

Per capita kilograms of oil equivalent

billion kilowatt hours

2010

2009

2010

2010

Costa Rica

–0.93

17.6

23,780

97

95

2.2

27

Côte d’Ivoire

–0.15

21.8

3,813

80

24

3.5

30

6.6

485

6.0

Croatia

–0.19

9.5

8,562

99

99

0.2

22

21.5

1,932

14.0

Cuba

–1.66

5.3

3,387

94

91

–0.1

15

31.6

975

17.4

Curacao

..

..

..

998

9.6

..

..

..

..

..

Cyprus

–0.09

4.5

699

100

100

1.4

27

8.2

2,215

Czech Republic

–0.08

15.1

1,253

100

98

–0.3

16

108.1

4,193

85.3

Denmark

–1.14

4.1

1,077

100

100

0.6

15

45.7

3,470

38.8

331

88

50

0.00

2.0

28

Dominica

0.58

3.7

..

..

..

0.1

20

0.1

..

..

Dominican Republic

0.00

24.1

2,088

86

83

2.1

14

20.3

840

15.9

Ecuador

1.81

38.0

29,456

94

92

2.2

19

30.1

836

17.7 146.8

–1.73

..

..

22

99

95

2.1

78

216.1

903

1.45

1.4

2,850

88

87

1.3

28

6.3

677

Equatorial Guinea

0.69

14.0

36,100

..

..

3.2

6

4.8

..

Eritrea

0.28

3.8

517

61

14

5.2

61

0.5

142

0.3

Estonia

0.12

22.6

9,486

98

95

0.1

9

16.0

4,155

13.0

Ethiopia

1.08

18.4

1,440

44

21

3.7

47

7.9

400

5.0

El Salvador

Faeroe Islands

0.00

Fiji

–0.34

6.1

0.5

.. 5.4

Djibouti

Egypt, Arab Rep.

0.0

..

8.3

..

..

..

..

0.8

100

100

0.6

15

53.6

6,787

80.7

3,057

100

100

1.2

12

363.4

4,031

564.3

French Polynesia

–3.97

0.1

..

100

98

1.1

..

0.9

..

..

14.6

106,892

33

2.3

7

87

68

1.6

1,418 ..

..

1.8

1.3

1,689

3.7

60

Georgia

0.09

3.4

12,958

98

95

1.0

49

5.8

700

10.1

Germany

0.00

42.3

1,308

100

100

0.2

16

734.6

4,003

622.1

Ghana

2.08

14.0

1,214

86

14

3.6

22

7.4

382

8.4

Greece

27

57.4

0.3

0.4

..

..

19,858

89

0.8

..

8.5 17.1

0.00

20

0.7

32,876

0.14 –0.39

–0.41

1.7

11

0.2

Finland

Gabon

83

..

France

Gambia, The

98

6.0

–0.81

9.9

5,133

100

98

94.9

2,440

Greenland

0.00

40.1

..

100

100

0.2

..

0.6

..

Grenada

0.00

0.1

..

..

97

1.3

19

0.2

..

..

.. ..

Guam

0.00

3.6

..

100

99

1.3

..

..

..

..

Guatemala

1.40

29.5

7,400

92

78

3.4

51

15.2

713

8.8

Guinea

0.54

6.4

22,110

74

18

3.8

55

1.2

..

..

Guinea-Bissau

0.48

26.9

10,342

64

20

3.6

48

0.3

..

..

4.8

318,766

Guyana

0.00

Haiti

94

0.5

17

3.8

35

77

3.1

34

7.7

601

6.7

0.4

15

48.7

2,567

37.4

16,882

0.1

1,285

13.9

12,371

87

–0.62

5.1

602

100

100

Iceland

–4.99

13.2

532,892

100

100

India

–0.46

Honduras

69

84

0.76 2.06

Hungary

1.6 2.3

.. 229

.. 0.6

18

2.0

4.8

1,165

2.5

52

1,979.4

Indonesia

0.51

6.4

8,332

82

54

2.5

60

451.8

867

169.8

Iran, Islamic Rep.

0.00

6.9

1,718

96

100

1.3

56

602.1

2,817

233.0

73

2.8

88

109.0

1,180

50.2

2.7

13

41.6

Iraq

–0.09

Ireland

–1.53

Isle of Man Israel

Economy

0.1

1,068

1.2

10,707

92

34

79 100

99

0.4

20

566

3,218

17.1 959.9

..

..

..

..

0.5

..

..

..

..

15.1

97

100

100

1.9

21

67.2

3,005

58.6

States and markets

Global links

Back

Statistics

28.4

0.00 –0.07

World Development Indicators 2013

47

Additional information about the data is provided in Primary data documentation, which summarizes national and international efforts to improve basic data collection and gives country-level information on primary sources, census years, fiscal years, statistical methods and concepts used, and other background information. Statistical methods provides technical information on some of the general calculations and formulas used throughout the book.

Symbols

Country notes

..

• Data for China do not include data for Hong Kong SAR, China; Macao SAR, China; or Taiwan, China. • Data for Indonesia include Timor-Leste through 1999. • Data for Mayotte, to which a reference appeared in previous editions, are included in data for France. • Data for Serbia do not include data for Kosovo or Monte­negro. • Data for Sudan include South Sudan unless otherwise noted.

means that data are not available or that aggregates cannot be calculated because of missing data in the years shown.

0 or means zero or small enough that the number would 0.0 round to zero at the displayed number of decimal places. /

in dates, as in 2010/11, means that the period of time, usually 12 months, straddles two calendar years and refers to a crop year, a survey year, or a fiscal year.

$

means current U.S. dollars unless otherwise noted.

<

means less than.

Economy

States and markets

Global links

Back

World Development Indicators 2013 xiii


User guide to WDI online tables Statistical tables that were previously available in the World Development Indicators print edition are now available online. Using an automated query process, these reference tables will be consistently updated based on the revisions to the World Development Indicators database.

How to access WDI online tables To access the WDI online tables, visit http://wdi.worldbank .org/tables. To access a specific WDI online table directly,

xivâ&#x20AC;&#x192;

World Development Indicators 2013

Front

?

User guide

use the URL http://wdi.worldbank.org/table/ and the table number (for example, http://wdi.worldbank.org/ table/1.1 to view the first table in the World view section). Each section of this book also lists the indicators included by table and by code. To view a specific indicator online, use the URL http://data.worldbank.org/ indicator/ and the indicator code (for example, http://data .worldbank.org/indicator/SP.POP.TOTL to view a page for total population).

World view

People

Environment


Breadcrumbs to show where youâ&#x20AC;&#x2122;ve been

Click on an indicator to view metadata

Click on a country to view metadata

How to use DataBank

Actions

DataBank (http://databank.worldbank.org) is an online web resource that provides simple and quick access to collections of time series data. It has advanced functions for selecting and displaying data, performing customized queries, downloading data, and creating charts and maps. Users can create dynamic custom reports based on their selection of countries, indicators, and years. All these reports can be easily edited, shared, and embedded as widgets on websites or blogs. For more information, see http://databank.worldbank.org/help.

Click to edit and revise the table in DataBank Click to print the table and corresponding indicator metadata Click to export the table to Excel Click to export the table and corresponding indicator metadata to PDF Click to access the WDI Online Tables Help file Click the checkbox to highlight cell level metadata and values from years other than those specified; click the checkbox again to reset to the default display

Economy

States and markets

Global links

Back

World Development Indicators 2013â&#x20AC;&#x192;xv


User guide to DataFinder

xvi 

DataFinder is a free mobile app that accesses the full set of data from the World Development Indicators database. Data can be displayed and saved in a table, chart, or map and shared via email, Facebook, and Twitter.

DataFinder works on mobile devices (smartphone or tablet computer) in both offline (no Internet connection) and online (Wi-Fi or 3G/4G connection to the Internet) modes.

• • • •

• View reports in table, chart, and map formats. • Send the data as a CSV file attachment to an email. • Share comments and screenshots via Facebook, ­Twitter, or email.

Select a topic to display all related indicators. Compare data for multiple countries. Select predefined queries. Create a new query that can be saved and edited later.

World Development Indicators 2013

Front

?

User guide

World view

People

Environment


Table view provides time series data tables of key development indicators by country or topic. A compare option shows the most recent yearâ&#x20AC;&#x2122;s data for the selected country and another country.

Chart view illustrates data trends and cross-country comparisons as line or bar charts.

Map view colors selected indicators on world and regional maps. A motion option animates the data changes from year to year.

Economy

States and markets

Global links

Back

World Development Indicators 2013â&#x20AC;&#x192;xvii


WORLD VIEW xviiiâ&#x20AC;&#x192;

World Development Indicators 2013

Front

?

User guide

World view People Environment


The Millennium Declaration adopted by all the members of the United Nations General Assembly in 2000 represents a commitment to a more effective, results-oriented development partnership in the 21st century. Progress documented here and in the annual reports of the United Nations Secretary-­General has been encouraging: poverty rates have fallen, more children— especially girls—are enrolled in and completing school, and they are—on average—living longer and healthier lives. Fewer mothers die in child birth, and more women have access to reproductive health services. The indicators used to monitor the Millennium Development Goals have traced the path of the HIV epidemic, the resurgence and retreat of tuberculosis, and the step-by-step efforts to “roll back malaria.” More people now have access to reliable water supplies and basic sanitation facilities. But forests continue to disappear and with them the habitat for many species of plants and animals, and greenhouse gases continue to accumulate in the atmosphere. From the start monitoring the Millennium Development Goals posed three challenges: selecting appropriate targets and indicators, constructing an international database for global monitoring, and significantly improving the quality, frequency, and availability of the relevant statistics. When they were adopted, the target year of 2015 seemed comfortably far away, and the baseline year of 1990 for measuring progress seemed a reasonable starting point with wellestablished data. As we near the end of that 25-year span, we have a better appreciation of how great those challenges were. Already there is discussion of the post2015 development agenda and the monitoring framework needed to record commitments and Economy

States and markets

measure progress. The Millennium Development Goals have contributed to the development of a statistical infrastructure that is increasingly capable of producing reliable statistics on various topics. The post-2015 agenda and a welldesigned monitoring framework will build on that infrastructure. The international database for monitoring the Millennium Development Goals is a valuable resource for analyzing many development issues. The effort of building and maintaining such a database should not be underestimated, and it will take several years to implement a new framework of goals and targets. To serve as an analytical resource, the database will need to include additional indicators, beyond those directly associated with the targets and the core data for conducting these indicators. New technologies and methods for reporting data should improve the quality and timeliness of the resulting database. The quality of data will ultimately depend on the capacity of national statistical systems, where most data originate. When the Millennium Development Goals were adopted, few developing countries had the capacity or resources to produce statistics of the requisite quality or frequency. Despite much progress, the statistical capacity-building programs initiated over the last decade should continue, and other statistical domains need attention. Planning for post-2015 goals must include concomitant plans for investments in statistics—by governments and development partners alike. The effort to achieve the Millennium Development Goals has been enormous. The next set of goals will require an even larger effort. Without good statistics, we will never know if we have succeeded. Global links

Back

1

World Development Indicators 2013 1


Goal 1 Eradicate extreme poverty Poverty rates continue to fall

1a

People living on less than 2005 PPP $1.25 a day (%) 75

Forecast 2010–15

Sub-Saharan Africa 50 South Asia

25 Europe & Central Asia

Latin America & Caribbean Middle East & North Africa 0

1990

1995

2000

2005

2010 estimate

2015 forecast

Source: World Bank PovcalNet.

Progress in reaching the poverty target, 1990–2010

1b

Share of countries making progress toward reducing poverty (%) 100

50

0

50 Reached target 100

On track

Off track

Seriously off track

East Asia

Europe Latin Middle East & Central America & & North Asia Caribbean Africa Source: World Bank staff calculations.

South Asia

Sub-Saharan Africa

Fewer people are living in extreme poverty

1c

People living on less than 2005 PPP $1.25 a day (billions) 2.0

Forecast 2010–15

Europe & Central Asia Latin America & Caribbean

1.5 Middle East & North Africa

1.0

0.5

0.0

South Asia Sub-Saharan Africa 1990

1995

2000

2005

2010 estimate

2015 forecast

Source: World Bank PovcalNet.

2 

World Development Indicators 2013

Front

?

User guide

The world will not have eradicated extreme poverty in 2015, but the Millennium Development Goal target of halving world poverty will have been met. The proportion of people living on less than $1.25 a day fell from 43.1 percent in 1990 to 22.7 percent in 2008, reaching new lows in all six developing country regions. While the food, fuel, and financial crises over the past five years worsened the situation of vulnerable populations and slowed poverty reduction in some countries, global poverty rates continued to fall in most regions. Preliminary estimates for 2010 confirm that the extreme poverty rate fell further, to 20.6 percent, reaching the global target five years early. Except in South Asia and Sub-­ Saharan Africa the target has also been met at the regional level (figure 1a). Fur ther progress is possible and likely before the 2015 target date of the Millennium Development Goals. Developing economies are expected to maintain GDP growth of 6.6–6.8 percent over the next three years, with growth of GDP per capita around 5.5 percent. Growth will be fastest in East Asia and Pacific and South Asia, which still contain more than half the world’s poorest people. Growth will be slower in Sub-­S aharan Africa, the poorest region in the world, but faster than in the preceding years, quickening the pace of poverty reduction. According to these forecasts, the proportion of people living in extreme poverty will fall to 16 percent by 2015. Based on current trends, 59 of 112 economies with adequate data are likely to achieve the first Millennium Development Goal (figure 1b). The number of people living in extreme poverty will continue to fall to less than a billion in 2015 (figure 1c). Of these, 40 percent will live in South Asia and 40 percent in Sub-­S aharan Africa. How fast poverty reduction will proceed depends not just on the growth of GDP but also on its distribution. Income distribution has improved in some countries, such as Brazil, while

World view People Environment


worsening in others, such as China. To speed progress toward eliminating extreme poverty, development strategies should attempt to increase not just the mean rate of growth but also the share of income going to the poorest part of the population. Sub-­Saharan Africa, where average income is low and average income of those below the poverty line is even lower, will face great difficulties in bringing the poorest people to an adequate standard of living (figure 1d). Latin America and the Caribbean, where average income is higher, must overcome extremely inequitable income distributions. Two Millennium Development Goal indicators address hunger and malnutrition. Child malnutrition, measured by comparing a child’s weight with that of other children of similar age, reflects a shortfall in food energy, poor feeding practices by mothers, and lack of essential nutrients in the diet. Malnutrition in children often begins at birth, when poorly nourished mothers give birth to underweight babies. Malnourished children develop more slowly, enter school later, and perform less well. Malnutrition rates have dropped substantially since 1990, from 28 percent of children under age 5 in developing countries to 17 percent in 2011. Every developing region except Sub-­S aharan Africa is on track to cut child malnutrition rates in half by 2015 (figure 1e). However, collecting data on malnutrition through surveys with direct measurement of children’s weight and height is costly, and many countries lack the information to calculate time trends. Undernourishment, a shortage of food energy to sustain normal daily activities, is affected by changes in the average amount of food available and its distribution. After steady declines in most regions from 1991 to 2005, further improvements in undernourishment have stalled, leaving 13 percent of the world’s population, almost 900 million people, without adequate daily food intake (figure 1f).

Economy

States and markets

Poorer than poor

1d

Average daily income of people living on less than 2005 PPP $1.25 a day, 2008 (2005 PPP $) 1.25

1.00

0.75

0.50

0.25

0.00

East Asia & Pacific

Europe & Central Asia

Latin America & Caribbean

Middle East & North Africa

South Asia

Sub-Saharan Africa

Source: World Bank PovcalNet.

Fewer malnourished children

1e

Malnutrition prevalence, weight for age (% of children under age 5) 60 South Asia

40 Sub-Saharan Africa

20

East Asia & Pacific Middle East & North Africa Europe & Central Asia Latin America & Caribbean

0

1990

1995

2000

2005

2011

Source: World Development Indicators database.

And fewer people lacking sufficient food energy

1f

Undernourishment prevalence (% of population) 40

30 Sub-Saharan Africa South Asia 20

Latin America & Caribbean

10

East Asia & Pacific

Middle East & North Africa Europe & Central Asia

0

1991

1996

2001

2006

2011

Source: Food and Agriculture Organization and World Development Indicators database.

Global links

Back

World Development Indicators 2013 3


Goal 2 Achieve universal primary education Growth in complete primary education has slowed

2a

Primary school completion rate (% of relevant age group) 125

East Asia & Pacific

Latin America & Caribbean

Europe & Central Asia 100

South Asia

75

Middle East & North Africa

Sub-Saharan Africa

50 25

0

1990

1995

2000

2005

2010

2015

Note: Dotted lines indicate progress needed to reach target. Source: United Nations Educational, Scientific and Cultural Organization Institute of Statistics and World Development Indicators database.

Progress toward universal  primary education, 1990–2010

2b

Share of countries making progress toward universal primary education (%) 100

50

0

50

100

Reached target Insufficient data

On track

Off track

Seriously off track

East Asia & Pacific

Europe Latin Middle East & Central America & & North Asia Caribbean Africa Source: World Bank staff calculations.

South Asia

Sub-Saharan Africa

More girls than boys remain out of school in most regions

2c

Children not attending primary school, 2010 (% of relevant age group) 30 25 20 15

0

Girls

5

Boys

10

Europe Latin Middle East South Sub-Saharan & Central America & & North Asia Africa Asia Caribbean Africa Source: United Nations Educational, Scientific and Cultural Organization Institute of Statistics and World Development Indicators database.

4 

World Development Indicators 2013

East Asia & Pacific

Front

?

User guide

The commitment to provide primary education to every child is the oldest of the Millennium Development Goals, having been set at the first Education for All conference in Jomtien, Thailand, more than 20 years ago. Progress among the poorest countries has accelerated since 2000, particularly in South Asia and Sub-­Saharan Africa, but full enrollment remains elusive. Many children start school but drop out before completion, discouraged by cost, distance, physical danger, and failure to progress. Even as countries approach the target, the education demands of modern economies expand, and primary education will increasingly be of value only as a stepping stone toward secondary and higher education. In most developing country regions school enrollment picked up after the Millennium Development Goals were promulgated in 2000, when the completion rate was 80 percent. Sub-­ Saharan Africa and South Asia, which started out farthest behind, made substantial progress. By 2009 nearly 90 percent of children in developing countries completed primary school, but completion rates have stalled since, with no appreciable gains in any region (figure  2a). Three regions have attained or are close to attaining complete primary education: East Asia and Pacific, Europe and Central Asia, and Latin America and the Caribbean (figure 2b). Completion rates in the Middle East and North Africa have stayed at 90 percent since 2008. South Asia has reached 88 percent, but progress has been slow. And Sub-­S aharan Africa lags behind at 70 percent. Even if the schools in these regions were to now enroll every eligible child in the first grade, they would not be able to achieve a full course of primary education by 2015. But it would help. Many children enroll in primary school but attend intermittently or drop out entirely. This is particularly true for girls—almost all school

World view People Environment


systems with low enrollment rates show under­ enrollment of girls in primary school, since their work is needed at home (figure 2c). Other obstacles discourage parents from sending their children to school, including the need for boys and girls during planting and harvest, lack of suitable school facilities, absence of teachers, and school fees. The problem is worst in South Asia and Sub-­Saharan Africa, where more than 46 million children of primary school age are not in school. Not all children have the same opportunities to enroll in school or remain in school. Across the world, children in rural areas are less likely to enter school, and when they do, they are likely to drop out sooner. In Ethiopia nearly all urban children complete first grade, but fewer than 80  percent of rural children do (figure  2d). In Senegal, where slightly more than 80 percent of urban children complete first grade, barely half of rural children begin the first grade and only 40  percent remain after nine years. Cambodia follows a similar pattern. Parents’ education makes a big difference in how far children go in school. In Nepal, for example, less than 90 percent of children whose parents lack any education complete first grade and barely 70 percent remain through the ninth (figure  2e). But 95  percent of children from households with some higher education stay through nine grades, and many of those go onto complete secondary school and enter tertiary education. Income inequality and educational quality are closely linked. Take Senegal (figure 2f). Children from wealthier households (as measured by a household’s ownership of certain assets) are more likely to enroll and stay in school than children from poorer households. Thus children from poor households are least likely to acquire the one asset—human capital—that could most help them to escape poverty.

Rural students at a disadvantage

2d

Share of people ages 10–19 completing each grade of schooling, by location, 2010–11 (%) 100

Urban Cambodia Urban Senegal

Urban Ethiopia

75 Rural Ethiopia

50

Rural Cambodia

Rural Senegal

25

0

Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9

Source: Demographic and Health Surveys and World Bank EdStats database.

Parents’ education makes a difference in Nepal

2e

Share of people ages 10–19 completing each grade of schooling, by parents’ education level, 2011 (%) Some higher

100

Incomplete primary

Primary

75

Incomplete secondary No education

50

25

0

Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9

Source: Demographic and Health Surveys and World Bank EdStats database.

Poverty is a barrier to education in Senegal

2f

Share of people ages 10–19 completing each grade of schooling, by wealth quintile, 2010 (%) 100 Wealthiest quintile 75

Fourth quintile Third quintile

50 Second quintile Poorest quintile

25

0

Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9

Source: Demographic and Health Surveys and World Bank EdStats database.

Economy

States and markets

Global links

Back

World Development Indicators 2013 5


Goal 3 Promote gender equality and empower women A ragged kind of parity in school enrollments

3a

Ratio of girls’ to boys’ gross enrollment, 2011 (%)

Primary

East Asia & Pacific

Secondary Tertiary

Europe & Central Asia

Latin America & Caribbean

Middle East & North Africa

South Asia

Sub-Saharan Africa

0

25

50

75

100

125

Source: United Nations Educational, Scientific and Cultural Organization Institute of Statistics and World Development Indicators database.

Progress toward gender equality in education, 1990–2010

3b

Share of countries making progress toward gender equality in primary and secondary education (%) 100

50

0

50

100

Reached target Insufficient data

On track

Off track

Seriously off track

Europe Latin Middle East & Central America & & North Asia Caribbean Africa Source: World Bank staff calculations.

6 

World Development Indicators 2013

East Asia & Pacific

Front

South Asia

?

Sub-Saharan Africa

User guide

Women make important contributions to economic and social development. Expanding opportunities for them in the public and private sectors is a core development strategy, and education is the starting point. By enrolling and staying in school, girls gains skills needed to enter the labor market, care for families, and make decisions for themselves. Achieving gender equality in education is an important demonstration that young women are full, contributing members of society. Girls have made substantial gains in school enrollment. In 1990 girls’ primary school enrollment rate in developing countries was only 86 percent of boys’. By 2011 it was 97 percent (figure 3a). Similar improvements have been made in secondary schooling, where girls’ enrollments have risen from 78 percent of boys’ to 96 percent over the same period. But the averages mask large differences across countries. At the end of 2011, 31 upper middle-income countries had reached or exceeded equal enrollment of girls in primary and secondary education, as had 23  lower middle-income countries but only 9 low-income countries. South Asia and Sub-­ Saharan Africa are lagging behind (figure 3b). Patterns of school attendance at the national level mirror those at the regional level: poor households are less likely than wealthy households to keep their children in school, and girls from wealthier households are more likely to enroll in school and stay longer. Ethiopia is just one example of the prevailing pattern documented by household surveys from many developing countries (figure 3c). More women are participating in public life at the highest levels. The proportion of parliamentary seats held by women continues to increase. In Latin America and the Caribbean women now hold 25 percent of all parliamentary seats (figure 3d). The most impressive gains have been made in the Middle East and North Africa, where the proportion of seats held by women more than tripled between 1990 and 2012. Algeria leads the way with 32 percent. In Nepal a third of parliamentary

World view People Environment


seats were held by women in 2012. Rwanda continues to lead the world. Since 2008, 56 percent of parliamentary seats have been held by women. Women work long hours and make important contributions to their families’ welfare, but many in the informal sector are unpaid for their labor. The largest proportion of women working in the formal sector is in Europe and Central Asia, where the median proportion of women in wage employment outside the agricultural sector was 46  percent (figure  3e). Latin America and the Caribbean is not far behind, with 42 percent of women in nonagricultural employment. Women’s share in paid employment in the nonagricultural sector has risen marginally but remains less than 20 percent in most countries in the Middle East and North Africa and South Asia and less than 35 percent in Sub-­Saharan Africa. In these regions full economic empowerment of women remains a distant goal. Lack of data hampers the ability to understand women’s roles in the economy. The Evidence and Data for Gender Equality (EDGE) Initiative is a new partnership, jointly managed by UN Women and the United Nations Statistics Division, in collaboration with member states, the World Bank, the Organisation for Economic Co-operation and Development, and others, that seeks to accelerate the work of gathering indicators on women’s education, employment, entrepreneurship, and asset ownership. During its initial phase EDGE will lay the ground work for a database of basic education and employment indicators, developing standards and guidelines for entrepreneurship and assets indicators, and pilot data in several countries. Relevant indicators could include the percentage distribution of the employed population, by sector and sex; the proportion of employed who are employer, by sex; the length of maternity leave; the percentage of firms owned by women; the proportion of the population with access to credit, by sex; and the proportion of the population who own land, by sex.

Economy

States and markets

Girls are disadvantaged at every income level in Ethiopia

3c

Share of people ages 10–19 completing each grade of schooling, by sex and wealth quintile, 2011 (%) 100

Wealthiest quintile, boys Wealthiest quintile, girls Third quintile, boys

75

Third quintile, girls

50 Poorest quintile, boys Poorest quintile, girls

25

0

Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9

Source: Demographic and Health Surveys and World Bank EdStats database.

More women in parliaments

3d

Share of seats held by women in national parliaments (%) 25

20 East Asia & Pacific Latin America & Caribbean

15

Europe & Central Asia

Sub-Saharan Africa

10

South Asia 5

0

Middle East & North Africa 1990

1995

2000

2005

2012

Source: Inter-Parliamentary Union and World Development Indicators database.

Women still lack opportunities in the labor market

3e

Share of women employed in the nonagricultural sector, median value, most recent year available, 2004–10 (% of total nonagricultural employment) 50 40 30 20 10 0

East Asia & Pacifica

Europe Latin Middle East South Sub-Saharan & Central America & & North Asia Africaa Asia Caribbean Africa a. Data cover less than two-thirds of regional population. Source: International Labour Organization and World Development Indicators database.

Global links

Back

World Development Indicators 2013 7


Goal 4 Reduce child mortality Under-five mortality rates continue to fall

4a

Under-five mortality rate (per 1,000 live births) 200

150 Sub-Saharan Africa 100 East Asia & Pacific

South Asia

50

Middle East & North Africa

Europe & Central Asia 0

1990

Latin America & Caribbean 1995

2000

2005

2011

Source: Inter-agency Group for Child Mortality Estimation and World Development Indicators database.

Progress toward reducing child mortality, 1990–2010

4b

Share of countries making progress toward reducing child mortality (%) 100

50

0

50

100

Reached target Insufficient data

On track

Off track

Seriously off track

East Asia & Pacific

Europe Latin Middle East & Central America & & North Asia Caribbean Africa Source: World Bank staff calculations.

South Asia

Sub-Saharan Africa

As mortality rates fall, a larger proportion of deaths occur in the first month

4c

Deaths of children under age 5, 2011 (millions) 4

Children (ages 1–4) Infants (ages 1–11 months) Neonatals (ages 0–1 month)

3

2

1

0

Europe Latin Middle East South Sub-Saharan & Central America & & North Asia Africa Asia Caribbean Africa Source: Inter-agency Group for Child Mortality Estimation and World Development Indicators database.

8 

World Development Indicators 2013

East Asia & Pacific

Front

?

User guide

In 1990, 12 million children died before their fifth birthday. By 1999 fewer than 10 million did. And in 2012 7 million did. In developing countries the under-five mortality rate fell from an average of 95 per 1,000 live births in 1990 to 56 in 2011, but rates in Sub-­Saharan Africa and South Asia remain much higher (figure 4a). Currently, 41 countries are poised to reach the Millennium Development Goal target of a two-thirds reduction in under-five mortality rates by 2015 (figure 4b). Faster improvements over the last decade suggest that many countries are accelerating progress and another 25 could reach the target as soon as 2020. Looking past 2015, still faster progress is possible if high mortality countries give priority to addressing the causes of child mortality. Concomitant reductions in fertility rates, particularly among adolescents, will also help. Most children die from causes that are readily preventable or curable with existing interventions, such as pneumonia (18 percent), diarrhea (11 percent), and malaria (7 percent). Almost 70 percent of deaths of children under age 5 occur in the first year of life, and 60 percent of those in the first month (figure 4c). Preterm birth complications account for 14 percent of deaths, and complications during birth another 9 percent (UN Inter-Agency Group for Child Mortality Estimation 2012). Therefore reducing child mortality requires addressing the causes of neonatal and infant deaths: inadequate care at birth and afterward, malnutrition, poor sanitation, and exposure to acute and chronic disease. Lower infant and child mortality rates are, in turn, the largest contributors to higher life expectancy in most countries. Childhood vaccinations are a proven, cost-­ effective way of reducing childhood illness and death. But despite years of vaccination campaigns, many children in low- and lower middle-income economies remain unprotected. To be successful, vaccination campaigns must reach all children and be sustained over time. Thus it is worrisome that measles vaccination rates in the two highest

World view People Environment


mortality regions, South Asia and Sub-­Saharan Africa, have stagnated in the last three years, at less than 80 percent coverage (figure 4d). Twenty countries in the developing world accounted for 4.5 million deaths among children under age 5 in 2011, or 65 percent of all such deaths worldwide (figure 4e). These countries are mostly large, often with high birth rates, but many have substantially reduced mortality rates over the past two decades. Of the 20, 11 have reached or are likely to achieve a two-thirds reduction in their under-five mortality rate by 2015: Bangladesh, Brazil, China, the Arab Republic of Egypt, Ethiopia, Indonesia, Madagascar, Malawi, Mexico, Niger, and Turkey. Had the mortality rates of 1990 prevailed in 2011, these 11 countries would have experienced 2 million more deaths. The remaining nine, where progress has been slower, have nevertheless averted 3 million deaths. If India were on track to reach the target, another 440,000 deaths would have been averted. The data used to monitor child mortality are produced by the Inter-agency Group for Child Mortality Estimation (IGME), which evaluates data from existing sources and then fits a statistical model to data points that are judged to be reliable. The model produces a trend line for under-five mortality rates in each country. Infant mortality and neonatal mortality rates are derived from under-five mortality estimates. The data come from household surveys and, where available, vital registration systems. But surveys are slow and costly. While they remain important tools for investigating certain complex, micro-level problems, vital registration systems are usually better sources of timely statistics. Recent IGME estimates of under-five mortality include new data from vital registration systems for about 70 countries. But many countries lack complete reporting of vital events, and even those that do often misreport cause of death. Vital registration supplemented by surveys and censuses offers the best approach for improving knowledge of morbidity and mortality in all age groups.

Economy

States and markets

Measles immunization rates are stagnating

4d

Children ages 12–23 months immunized against measles (%) 100

Europe & Central Asia

East Asia & Pacific

Middle East & North Africa 75

Latin America & Caribbean

South Asia

Sub-Saharan Africa

50

25

0

1990

1995

2000

2005

2011

Source: World Health Organization, United Nations Children’s Fund, and World Development Indicators database.

Five million deaths averted in 20 countries

4e

Deaths of children under age 5, 2011 (millions) At 2011 mortality rate

Averted based on 1990 mortality rate

India Nigeria China Pakistan Ethiopia Bangladesh Indonesia Tanzania Afghanistan Uganda Niger Mozambique Angola Brazil Egypt, Arab Rep. Malawi Philippines Madagascar Mexico Turkey 0

1

2

3

4

Source: World Bank staff calculations.

Global links

Back

World Development Indicators 2013 9


Goal 5 Improve maternal health Maternal deaths are more likely in South Asia and Sub-­Saharan Africa

5a

Maternal mortality ratio, modeled estimate (per 100,000 live births) 1,000 Sub-Saharan Africa 750 South Asia 500

250

Latin America & Caribbean

Middle East & North Africa East Asia & Pacific

0

Europe & Central Asia 1990

1995

2000

2005

2010

Source: Maternal Mortality Estimation Inter-Agency Group and World Development Indicators database.

Progress toward reducing maternal mortality, 1990–2010

5b

Share of countries making progress toward reducing maternal mortality (%) 100

50

0

50

100

Reached target Insufficient data

On track

Off track

Seriously off track

East Asia & Pacific

Europe Latin Middle East & Central America & & North Asia Caribbean Africa Source: World Bank staff calculations.

South Asia

Sub-Saharan Africa

Reducing the risk to mothers

5c

Lifetime risk of maternal death (%) 6

4

2010

0

1990

2

Europe Latin Middle East South Sub-Saharan & Central America & & North Asia Africa Asia Caribbean Africa Source: Maternal Mortality Estimation Inter-Agency Group and World Development Indicators database.

10 

World Development Indicators 2013

East Asia & Pacific

Front

?

User guide

An estimated 287,000 maternal deaths occurred worldwide in 2010, all but 1,700 of them in developing countries. More than half of maternal deaths occur in Sub-­S aharan Africa and a quarter in South Asia. And while the number of maternal deaths remains high, South Asia has made great progress in reducing them, reaching a maternal mortality ratio of 220 per 100,000 live births in 2010, down from 620 in 1990, a drop of 65 percent. The Middle East and North Africa and East Asia and Pacific have also reduced their maternal morality ratios more than 60 percent (figure 5a). These are impressive achievements, but progress in reducing maternal mortality has been slow, far slower than targeted by the Millennium Development Goals, which call for reducing the maternal mortality ratio by 75 percent between 1990 and 2015. But few countries and no developing region on average will achieve this target. Based on progress through 2010, 8 countries have achieved a 75 percent reduction, and 10 more are on track to reach the 2015 target (figure 5b). This is an improvement over the 2008 assessment, suggesting that progress is accelerating. Because of the reductions in Cambodia, China, Lao People’s Democratic Republic, and Vietnam, 74 percent of people in East Asia and Pacific live in a country that has reached the target (Vietnam) or is on track to do so by 2015. On average a third of people in low- and middleincome countries live in countries that have reached the target or are on track to do so. The maternal mortality ratio gives the risk of a maternal death at each birth, a risk compounded with each pregnancy. And because women in poor countries have more children under riskier conditions, their lifetime risk of maternal death may be 100 times greater than for women in highincome countries. Improved health care and lower fertility rates have reduced the lifetime risk in all regions, but women ages 15–49 in Sub-­Saharan Africa still face a 2.5 percent chance of dying

World view People Environment


in childbirth, down from more than 5 percent in 1990 (figure 5c). In Chad and Somalia, both fragile states, lifetime risk is still more than 6  percent, meaning more than 1 woman in 16 will die in childbirth. Reducing maternal mortality requires a comprehensive approach to women’s reproductive health, starting with family planning and access to contraception. In countries with data half of women who are married or in union use some method of birth control. Household surveys of women show that some 200 million women want to delay or cease childbearing, and a substantial proportion say that their last birth was unwanted or mistimed (United Nations 2012). Figure 5d shows the share of women of childbearing age who say they need but are not using contraception. There are large differences within each region. More surveys have been carried out in Sub-­Saharan Africa than in any other region, and many show a large unmet need for family planning. Women who give birth at an early age are likely to bear more children and are at greater risk of death or serious complications from pregnancy. The adolescent birth rate is highest in Sub-­ Saharan Africa and is declining slowly. A rapid decrease in South Asia has been led by Maldives, Afghanistan, and Pakistan (figure 5e). Many health problems among pregnant women are preventable or treatable through visits with trained health workers before childbirth. Skilled attendants at delivery and access to hospital treatments are essential for dealing with lifethreatening emergencies such as severe bleeding and hypertensive disorders. In South Asia and Sub-­Saharan Africa fewer than half of births are attended by doctors, nurses, or trained midwives (figure 5f). Having skilled health workers present for deliveries is key to reducing maternal mortality. In many places women have only untrained caregivers or family members to attend them during childbirth.

Economy

States and markets

A wide range of needs

5d

Unmet need for contraception, most recent year available, 2006–10 (% of women married or in union ages 15–49) 50

Regional median

40

30 20

10 0

East Asia & Pacific

(7 countries)

Europe & Central Asia

(10 countries)

Latin America & Caribbean

(9 countries)

Middle East & North Africa

South Asia

(5 countries)

Sub-Saharan Africa (31 countries)

(6 countries)

Source: Demographic and Household Surveys, Multiple Indicator Cluster Surveys, and World Development Indicators database.

Fewer young women giving birth

5e

Adolescent fertility rate (births per 1,000 women ages 15–19) 150 Sub-Saharan Africa South Asia 100 Latin America & Caribbean 50

Middle East & North Africa Europe & Central Asia East Asia & Pacific

0

1997

1999

2001

2003

2005

2007

2009

2011

Source: United Nations Population Division and World Development Indicators database.

Every mother needs care

5f

Births attended by skilled health staff, average of most recent year available for 2007–11 (% of total) 100

75

50

25

0

East Asia & Pacific

Europe Latin Middle East South Sub-Saharan & Central America & & North Asia Africa Asia Caribbeana Africaa a. Data are for 1998–2002. Source: United Nations Children’s Fund and World Development Indicators database.

Global links

Back

World Development Indicators 2013 11


Goal 6 Combat HIV/AIDS, malaria, and other diseases HIV prevalence in Sub-­Saharan Africa continues to fall

6a

HIV prevalence (% of population ages 15–49) 6

Sub-Saharan Africa

5 4 3 2

Latin America & Caribbean High income

1 0

Other developing regions

1990

1995

2000

2005

2011

Source: Joint United Nations Programme on HIV/AIDS and World Development Indicators database.

Progress toward halting and reversing the HIV epidemic, 1990–2010

6b

Share of countries making progress against HIV/AIDS (%) 100

50

0

50 Halted and reversed Not improving

100

Halted or reversed Insufficient data

Stable low prevalence

East Asia & Pacific

Europe Latin Middle East & Central America & & North Asia Caribbean Africa Source: World Bank staff calculations.

South Asia

Sub-Saharan Africa

Knowledge to control HIV/AIDS

6c

People with comprehensive and correct knowledge about HIV, most recent year available (% of adults ages 15–49) 75

50

nia za Ta n

da

Ke ny a

Ug an

Mo z

Ma law i

mb ia am biq ue

bia

Za

mi Na

o th

ba Zim

d ila n az Sw

Le so

0

bw e

Women Men

25

Epidemic diseases exact a huge toll in human suffering and lost opportunities for development. Poverty, armed conflict, and natural disasters contribute to the spread of disease and are made worse by it. In Africa the spread of HIV/AIDS has reversed decades of improvement in life expectancy and left millions of children orphaned. Malaria takes a large toll on young children and weakens adults at great cost to their productivity. Tuberculosis killed 1.4 million people in 2010, most of them ages 15–45, and sickened millions more. There were 34 million people living with HIV/ AIDS in 2011, and 2.5 million more people acquired the disease. Sub-­Saharan Africa remains the center of the HIV/AIDS epidemic, but the proportion of adults living with AIDS has begun to fall even as the survival rate of those with access to antiretroviral drugs has increased (figures 6a and 6b). By the end of 2010, 6.5 million people worldwide were receiving antiretroviral drugs. This represented the largest one-year increase in coverage but still fell far short of universal access (United Nations 2012). Altering the course of the HIV epidemic requires changes in behaviors by those already infected by the virus and those at risk of becoming infected. Knowledge of the cause of the disease, its transmission, and what can be done to avoid it is the starting point. The ability to reject false information is another important kind of knowledge. But significant gaps in knowledge remain. In 26 of 31 countries with a generalized epidemic and in which nationally representative surveys were carried out recently, less than half of young women have comprehensive and correct knowledge about HIV (UNAIDS 2012). And less than half of men in 21 of 25 countries had correct knowledge. In only

Note: Comprehensive and correct knowledge about HIV entails knowledge of two ways to prevent HIV and rejecting three misconceptions. Source: Joint United Nations Programme on HIV/AIDS and World Development Indicators database.

12 

World Development Indicators 2013

Front

?

User guide

World view People Environment


3 of the 10 countries with the highest HIV prevalence rates in 2011 did more than half the men and women tested demonstrate knowledge of two ways to prevent HIV and reject three misconceptions (figure 6c). In Kenya men scored better than 50  percent, but women fell short. Clearly more work is to be done. In 2011 there were 8.8  million people newly diagnosed with tuberculosis, but incidence, prevalence, and death rates from tuberculosis are falling (figure 6d). If these trends are sustained, the world could achieve the target of halting and reversing the spread of this disease by 2015. People living with HIV/AIDS, which reduces resistance to tuberculosis, are particularly vulnerable, as are refugees, displaced persons, and prisoners living in close quarters and unsanitary conditions. Well-managed medical intervention using appropriate drug therapy is crucial to stopping the spread of tuberculosis. There are 300–500 million cases of malaria each year, causing more than 1 million deaths. Malaria is a disease of poverty. But there has been progress against it. In 2011 Armenia was added to the list of countries certified free of the disease. Although malaria occurs in all regions, Sub-­Saharan Africa is where the most lethal form of the malaria parasite is most abundant. Insecticide-treated nets have proved to be an effective preventative, and their use in the region is growing: from 2 percent of the population under age 5 in 2000 to 39 percent in 2010 (figure 6e). Better testing and the use of combination therapies with artemisinin-based drugs are improving the treatment of at-risk populations. But malaria is difficult to control. There is evidence of emerging resistance to artemisinins and to pyrethroid insecticides used to treat mosquito nets.

Fewer people contracting, living with, and dying from tuberculosis

6d

Tuberculosis prevalence, incidence, and deaths in low- and middle-income countries (per 100,000 people) 400 Prevalence 300

200 Incidence 100 Deaths 0

1990

1995

2000

2005

2011

Source: World Health Organization and World Development Indicators database.

Use of insecticide-treated nets increasing in Sub- ­Saharan Africa

6e

Use of insecticide-treated nets (% of population under age 5) First observation (2000 or earlier)

Most recent observation (2006 or later)

Swaziland Côte d’Ivoire Guinea Comoros Zimbabwe Chad Somalia Mozambique Benin Cameroon Sudan Angola Nigeria Sierra Leone Ethiopia Gambia, The Namibia Senegal Guinea-Bissau Central African Rep. Liberia Congo, Dem. Rep. Ghana Malawi Uganda Burundi Madagascar Kenya Burkina Faso Eritrea Zambia Gabon São Tomé and Príncipe Togo Tanzania Niger Rwanda Mali Congo, Rep. (2005) Mauritania (2004) 0

20

40

60

80

Source: United Nations Children’s Fund and World Development Indicators database.

Economy

States and markets

Global links

Back

World Development Indicators 2013 13


Goal 7 Ensure environmental sustainability Carbon dioxide emissions dropped slightly in 2009

7a

Carbon dioxide emissions (millions of metric tons) 40

30

20

High income

10 Upper middle income 0

Low income

Lower middle income 1990

1995

2000

2005

2009

Source: Carbon Dioxide Information Analysis Center and World Development Indicators database.

Forest losses and gains

7b

Average annual change in forest area (thousands of square kilometers)

1990–2000

0

–250

–500

2000–10

250

East Asia & Pacific

Europe Latin Middle East South Sub-Saharan High & Central America & & North Asia Africa income Asia Caribbean Africa Source: Food and Agriculture Organization and World Development Indicators database.

Better access to improved water sources

7c

Share of population with access to improved water sources (%) 100

75

50

2010

0

1990

25

Europe Latin Middle East South Sub-Saharan & Central America & & North Asia Africa Asia Caribbean Africa Source: Joint Monitoring Programme of the World Health Organization and United Nations Children’s Fund and World Development Indicators database.

14 

World Development Indicators 2013

East Asia & Pacific

Front

?

User guide

The seventh goal of the Millennium Development Goals is the most far-reaching, affecting each person now and in the future. It addresses the condition of the natural and built environments: reversing the loss of natural resources, preserving biodiversity, increasing access to safe water and sanitation, and improving living conditions of people in slums. The overall theme is sustainability, an equilibrium in which people’s lives can improve without depleting natural and manmade capital stocks. The failure to reach a comprehensive agreement on limiting greenhouse gas emissions leaves billions of people vulnerable to climate change. Although the global financial crisis caused a slight decrease in carbon dioxide emissions, such emissions are expected to rise as economic activity resumes in large industrial economies (figure 7a). The loss of forests threatens the livelihood of poor people, destroys the habitat that harbors biodiversity, and eliminates an important carbon sink that helps moderate the climate. Net losses since 1990 have been substantial, especially in Latin American and the Caribbean and Sub-­Saharan Africa, and only partly compensated by net gains elsewhere. The rate of deforestation slowed in the past decade, but on current trends zero net losses will not be reached for another 20 years (figure 7b). Protecting forests and other terrestrial and marine areas helps protect plant and animal habitats and preserve the diversity of species. By 2010, 13  percent of the world’s land area had been protected, but only 1.6 percent of oceans had similar protection. Such measures have slowed the rate of species extinction, but substantial losses continue (United Nations 2012). The Millennium Development Goals call for halving the proportion of the population without access to improved sanitation facilities and water sources by 2015. In 1990 more than 1 billion people lacked access to drinking water from a convenient, protected source. In developing countries the proportion of people with access to an

World view People Environment


Economy

States and markets

Rural areas lack sanitation facilities

7d

Share of population with access to improved sanitation facilities, 2010 (%) 100

75

50

0

Urban

25 Rural

improved water source rose from 71 percent in 1990 to 86 in 2010 (figure 7c). In 1990 only 37 percent of the people living in low- and middle-income economies had access to a flush toilet or other form of improved sanitation. By 2010 the access rate had risen to 56  percent. But 2.7 billion people still lack access to improved sanitation, and more than 1 billion practice open defecation, posing enormous health risks. The situation is worse in rural areas, where 43 percent of the population have access to improved sanitation; in urban areas the access rate is 30 percentage points higher (figure 7d). This large disparity, especially in South Asia and Sub-­Saharan Africa, is the principal reason the sanitation target of the Millennium Development Goals will not be met. Achieving sustainable development also requires managing natural resources carefully, since high economic growth can deplete natural capital, such as forests and minerals. Countries that rely heavily on extractive industries have seen large increases in natural resource rents, but their growth will not be sustainable unless they invest in productive assets, including human capital (figure 7e). The World Bank has constructed a global database to monitor the sustainability of economic progress using wealth accounts, including indicators of adjusted net savings and adjusted net national income. Wealth is defined comprehensively to include stocks of manufactured capital, natural capital, human capital, and social capital. Development is conceived as building wealth and managing a portfolio of assets. The challenge of development is to manage not just the total volume of assets but also the composition of the asset portfolio—that is, how much to invest in different types of capital. Adjusted net savings is a sustainability indicator that measures whether a country is building its wealth sustainably (positive values) or running it down on an unsustainable development path (negative values; figure 7f).

East Asia & Pacific

Europe Latin Middle East South Sub-Saharan & Central America & & North Asia Africa Asia Caribbean Africa Source: Joint Monitoring Programme of the World Health Organization and United Nations Children’s Fund and World Development Indicators database.

Resource rents are a large share of GDP in Africa and the Middle East

7e

Resource rents (% of GDP) 50

40

Middle East & North Africa

30

Europe & Central Asia

20 Sub-Saharan Africa 10

0

East Asia & Pacific South Asia

Latin America & Caribbean 1990

1995

2000

2005

2010

Source: World Bank staff calculations and World Development Indicators database.

A nonsustainable path in Sub‑Saharan Africa

7f

Share of gross national income, 2008 (%) 20 Depreciation of fixed capital

Education expenditures

10

Depletion of natural resources

0

Pollution damages

–10

Gross savings

Net savings

Net savings plus education expeditures

Depletion adjusted savings

Adjusted net savings

Source: World Bank 2011.

Global links

Back

World Development Indicators 2013 15


Goal 8 Develop a global partnership for development Aid flows decline

8a

Official development assistance from Development Assistance Committee members (2010 $ billions) 200 Humanitarian assistance

150 Net debt relief

100

Bilateral net official development assistance, excluding debt relief and humanitarian assistance

50

0

Multilateral net official development assistance, excluding debt relief and humanitarian assistance

1990

1995

2000

2005

2011

Source: Organisation for Economic Co-operation and Development StatExtracts.

Domestic subsidies to agriculture exceed aid flows

8b

Agricultural support ($ billions) 150

European Union 100 Japan 50 United States Korea, Rep. 0

Turkey 1990

1995

2000

2005

2011

Source: Organisation for Economic Co-operation and Development StatExtracts.

More opportunities for exporters in developing countries

8c

Goods (excluding arms) admitted free of tariffs from developing countries (% total merchandise imports, excluding arms) 100 United States

Norway 75

Australia Japan

50 European Union 25

0

1996

1998

2000

2002

2004

2006

2008

2010

Source: World Trade Organization, International Trade Center, United Nations Conference on Trade and Development, and World Development Indicators database.

16 

World Development Indicators 2013

Front

?

User guide

The eighth and final goal distinguishes the Millennium Development Goals from previous resolutions and targeted programs. It recognizes the multidimensional nature of development and the need for wealthy countries and developing countries to work together to create an environment in which rapid, sustainable development is possible. Along with increased aid flows and debt relief for the poorest, highly indebted countries, goal 8 recognizes the need to reduce barriers to trade and to share the benefits of new medical and communication technologies. It is also a reminder that development challenges differ for large and small countries and for those that are landlocked or isolated by large expanses of ocean. Building and sustaining a partnership is an ongoing process that does not stop at a specific date or when a target is reached. After falling through much of the 1990s, official development assistance (ODA) from members of the Organisation for Economic Co-operation and Development’s (OECD) Development Assistance Committee (DAC) rose sharply after 2002, but a large part of the increase was in the form of debt relief and humanitarian assistance (figure 8a). The financial crisis that began in 2008 and fiscal austerity in many high-income economies have begun to undermine commitments to increase ODA. Net disbursements of ODA by members of the DAC rose to $134 billion in 2011, but, after accounting for price and exchange rate adjustments, fell 2.3 percent in real terms from 2010. Aid from multilateral organizations remained essentially unchanged at $34.7 billion, a decrease of 6.6 percent in real terms. ODA from DAC members has fallen back to 0.31 percent of their combined gross national income, less than half the UN target of 0.7 percent. OECD members, mostly high-income economies but also some upper middle-income economies such as Chile, Mexico, and Turkey, continue to spend more on support to domestic agricultural producers than on ODA. In 2011 the OECD

World view People Environment


estimate of agricultural subsidies was $252 billion, 41  percent of which was to EU producers (figure 8b). Many rich countries have pledged to open their markets to exports from developing countries, and the share of goods (excluding arms) admitted duty free by OECD economies has been rising. However, arcane rules of origin and phytosanitary standards keep many countries from qualifying for duty-free access. And uncertainty over market access may inhibit development of export industries (figure 8c). Growing economies, better debt management, and debt relief for the poorest countries have allowed developing countries to substantially reduce their debt burdens. Despite the financial crisis and a 2.3 percent contraction in the global economy in 2009, the debt service to exports ratio in low- and middle-income economies reached a new low of 8.8 percent in 2011. In Europe and Central Asia, where the debt service to exports ratio rose to 26 percent in 2009, higher export earnings have helped return the average to its 2007 level of 17.8 percent (figure 8d). Telecommunications is an essential tool for development, and new technologies are creating new opportunities everywhere. The growth of fixedline phone systems has peaked in high-income economies and will never reach the same level of use in developing countries. In high-income economies mobile phone subscriptions have now passed 1 per person, and upper middle-income economies are not far behind (figure 8e). Mobile phones are one of several ways of accessing the Internet. In 2000 Internet use was spreading rapidly in high-income economies but was barely under way in developing country regions. Now developing countries are beginning to catch up. Since 2000 Internet use per person in developing economies has grown 28 percent a year. Like telephones, Internet use is strongly correlated with income. The low-income economies of South Asia and Sub-­Saharan Africa lag behind, but even there Internet access is spreading rapidly (figure 8f).

Economy

States and markets

Debt service burdens continue to fall

8d

Total debt service (% of exports of goods, services, and income) 50 Latin America & Caribbean

40 South Asia

Europe & Central Asia

30

20 East Asia & Pacific

10

Sub-Saharan Africa 0

Middle East & North Africa 1990

1995

2000

2005

2011

Source: World Development Indicators database.

Telecommunications on the move

8e

Mobile phone subscriptions (per 100 people) 125 High income 100 Upper middle income

75

50

Lower middle income

25 Low income 0

1990

1995

2000

2005

2011

Source: International Telecommunications Union and World Development Indicators database.

More people connecting to the Internet

8f

Internet users (per 100 people) 80 High income

60

Europe & Central Asia 40 Latin America & Caribbean East Asia & Pacific 20

0

Sub-Saharan Africa

Middle East & North Africa

South Asia 2000

2002

2004

2006

2008

2011

Source: International Telecommunications Union and World Development Indicators database.

Global links

Back

World Development Indicators 2013 17


Millennium Development Goals

Goals and targets from the Millennium Declaration Indicators for monitoring progress Goal 1 Eradicate extreme poverty and hunger Target 1.A Halve, between 1990 and 2015, the proportion of people whose income is less than $1 a day

Target 1.B Achieve full and productive employment and decent work for all, including women and young people

Target 1.C Halve, between 1990 and 2015, the proportion of people who suffer from hunger Goal 2 Achieve universal primary education Target 2.A Ensure that by 2015 children everywhere, boys and girls alike, will be able to complete a full course of primary schooling Goal 3 Promote gender equality and empower women Target 3.A Eliminate gender disparity in primary and secondary education, preferably by 2005, and in all levels of education no later than 2015

Goal 4 Reduce child mortality Target 4.A Reduce by two-thirds, between 1990 and 2015, the under-five mortality rate

Goal 5 Improve maternal health Target 5.A Reduce by three-quarters, between 1990 and 2015, the maternal mortality ratio Target 5.B Achieve by 2015 universal access to reproductive health

Goal 6 Combat HIV/AIDS, malaria, and other diseases Target 6.A Have halted by 2015 and begun to reverse the spread of HIV/AIDS

Target 6.B Achieve by 2010 universal access to treatment for HIV/AIDS for all those who need it Target 6.C Have halted by 2015 and begun to reverse the incidence of malaria and other major diseases

1.1 Proportion of population below $1 purchasing power parity (PPP) a daya 1.2 Poverty gap ratio [incidence × depth of poverty] 1.3 Share of poorest quintile in national consumption 1.4 Growth rate of GDP per person employed 1.5 Employment to population ratio 1.6 Proportion of employed people living below $1 (PPP) a day 1.7 Proportion of own-account and contributing family workers in total employment 1.8 Prevalence of underweight children under five years of age 1.9 Proportion of population below minimum level of dietary energy consumption 2.1 Net enrollment ratio in primary education 2.2 Proportion of pupils starting grade 1 who reach last grade of primary education 2.3 Literacy rate of 15- to 24-year-olds, women and men 3.1 Ratios of girls to boys in primary, secondary, and tertiary education 3.2 Share of women in wage employment in the nonagricultural sector 3.3 Proportion of seats held by women in national parliament 4.1 Under-five mortality rate 4.2 Infant mortality rate 4.3 Proportion of one-year-old children immunized against measles 5.1 5.2 5.3 5.4 5.5

Maternal mortality ratio Proportion of births attended by skilled health personnel Contraceptive prevalence rate Adolescent birth rate Antenatal care coverage (at least one visit and at least four visits) 5.6 Unmet need for family planning 6.1 HIV prevalence among population ages 15–24 years 6.2 Condom use at last high-risk sex 6.3 Proportion of population ages 15–24 years with comprehensive, correct knowledge of HIV/AIDS 6.4 Ratio of school attendance of orphans to school attendance of nonorphans ages 10–14 years 6.5 Proportion of population with advanced HIV infection with access to antiretroviral drugs 6.6 Incidence and death rates associated with malaria 6.7 Proportion of children under age five sleeping under insecticide-treated bednets 6.8 Proportion of children under age five with fever who are treated with appropriate antimalarial drugs 6.9 Incidence, prevalence, and death rates associated with tuberculosis 6.10 Proportion of tuberculosis cases detected and cured under directly observed treatment short course

Note: The Millennium Development Goals and targets come from the Millennium Declaration, signed by 189 countries, including 147 heads of state and government, in September 2000 (www.un.org/millennium/declaration/ares552e.htm) as updated by the 60th UN General Assembly in September 2005. The revised Millennium Development Goal (MDG) monitoring framework shown here, including new targets and indicators, was presented to the 62nd General Assembly, with new numbering as recommended by the Inter-agency and Expert Group on MDG Indicators at its 12th meeting on November 14, 2007. The goals and targets are interrelated and should be seen as a whole. They represent a partnership between the developed countries and the developing countries “to create an environment—at the national and global levels alike—which is conducive to development and the elimination of poverty.” All indicators should be disaggregated by sex and urban-rural location as far as possible.

18 

World Development Indicators 2013

Front

?

User guide

World view People Environment


Goals and targets from the Millennium Declaration Indicators for monitoring progress Goal 7 Ensure environmental sustainability Target 7.A Integrate the principles of sustainable development into country policies and programs and reverse the loss of environmental resources Target 7.B Reduce biodiversity loss, achieving, by 2010, a significant reduction in the rate of loss

Target 7.C Halve by 2015 the proportion of people without sustainable access to safe drinking water and basic sanitation Target 7.D Achieve by 2020 a significant improvement in the lives of at least 100 million slum dwellers Goal 8 Develop a global partnership for development Target 8.A Develop further an open, rule-based, predictable, nondiscriminatory trading and financial system

7.1 Proportion of land area covered by forest 7.2 Carbon dioxide emissions, total, per capita and per $1 GDP (PPP) 7.3 Consumption of ozone-depleting substances 7.4 Proportion of fish stocks within safe biological limits 7.5 Proportion of total water resources used 7.6 Proportion of terrestrial and marine areas protected 7.7 Proportion of species threatened with extinction 7.8 Proportion of population using an improved drinking water source 7.9 Proportion of population using an improved sanitation facility 7.10 Proportion of urban population living in slumsb

Some of the indicators listed below are monitored separately for the least developed countries (LDCs), Africa, landlocked developing countries, and small island developing states.

(Includes a commitment to good governance, development, and poverty reduction—both nationally and internationally.)

Target

Target

Target

Target

Target

Official development assistance (ODA) 8.1 Net ODA, total and to the least developed countries, as percentage of OECD/DAC donors’ gross national income 8.2 Proportion of total bilateral, sector-allocable ODA of OECD/DAC donors to basic social services (basic education, primary health care, nutrition, safe water, and 8.B Address the special needs of the least developed sanitation) countries 8.3 Proportion of bilateral official development assistance of OECD/DAC donors that is untied (Includes tariff and quota-free access for the least developed countries’ exports; enhanced program of 8.4 ODA received in landlocked developing countries as a proportion of their gross national incomes debt relief for heavily indebted poor countries (HIPC) 8.5 ODA received in small island developing states as a and cancellation of official bilateral debt; and more proportion of their gross national incomes generous ODA for countries committed to poverty reduction.) Market access 8.C Address the special needs of landlocked 8.6 Proportion of total developed country imports (by value developing countries and small island developing and excluding arms) from developing countries and least states (through the Programme of Action for developed countries, admitted free of duty the Sustainable Development of Small Island 8.7 Average tariffs imposed by developed countries on Developing States and the outcome of the 22nd agricultural products and textiles and clothing from special session of the General Assembly) developing countries 8.8 Agricultural support estimate for OECD countries as a percentage of their GDP 8.9 Proportion of ODA provided to help build trade capacity 8.D Deal comprehensively with the debt problems of developing countries through national and Debt sustainability international measures in order to make debt 8.10 Total number of countries that have reached their HIPC sustainable in the long term decision points and number that have reached their HIPC completion points (cumulative) 8.11 Debt relief committed under HIPC Initiative and Multilateral Debt Relief Initiative (MDRI) 8.12 Debt service as a percentage of exports of goods and services 8.E In cooperation with pharmaceutical companies, 8.13 Proportion of population with access to affordable provide access to affordable essential drugs in essential drugs on a sustainable basis developing countries 8.F In cooperation with the private sector, make 8.14 Fixed-line telephones per 100 population available the benefits of new technologies, 8.15 Mobile cellular subscribers per 100 population especially information and communications 8.16 Internet users per 100 population

a. Where available, indicators based on national poverty lines should be used for monitoring country poverty trends. b. T he proportion of people living in slums is measured by a proxy, represented by the urban population living in households with at least one of these characteristics: lack of access to improved water supply, lack of access to improved sanitation, overcrowding (three or more people per room), and dwellings made of nondurable material.

Economy

States and markets

Global links

Back

World Development Indicators 2013 19


1  World view Population

Population density

Urban population

Gross national income

millions

thousand sq. km

people per sq. km

% of total population

$ billions

Per capita $

$ billions

Per capita $

% growth

Per capita % growth

2011

2011

2011

2011

2011

2011

Atlas method

Purchasing power parity

2011

2011

35.3

652.2

54

24

16.6

470

Albania

3.2

28.8

117

53

12.8

Algeria

36.0

2,381.7

15

73

160.8

American Samoa

0.1

0.2

348

93

..

..b

..

Andorra

0.1

0.5

183

87

..

..c

..

19.6

1,246.7

16

59

75.2

3,830 d

102.7

Afghanistan

Angola Antigua and Barbuda

Gross domestic product

2010–11

2010–11

40.3a

1,140a

5.7

2.9

3,980

28.4

8,820

3.0

2.6

4,470

299.0a

8,310a

2.5

1.0

..

..

..

..

..

..

5,230

3.9

1.1

17,900a

–5.0

–6.0

1.6a

0.1

0.4

204

30

1.1

11,940

40.8

2,780.4

15

93

..

..

..

..

..

..

Armenia

3.1

29.7

109

64

10.4

3,360

18.9

6,100

4.6

4.3

Aruba

0.1

0.2

601

47

..

..

..

..

..

22.3

7,741.2

3

89

1,111.4

49,790

862.0

38,610

1.9

0.7

Austria

8.4

83.9

102

68

405.7

48,170

354.0

42,030

2.7

2.3

Azerbaijan

9.2

86.6

111

54

48.5

5,290

82.1

8,950

1.0

–0.3

Bahamas, The

0.3

13.9

35

84

7.5

21,970

10.2a

29,790a

1.6

0.4

Bahrain

1.3

0.8

1,742

89

20.1

15,920

26.8

21,200

3.0

–3.1

150.5

144.0

1,156

28

117.8

780

291.7

0.3

0.4

637

44

3.5

12,660

Belarus

9.5

207.6

47

75

55.2

5,830

137.0

Belgium

11.0

30.5

364

98

506.2

45,930

431.4

0.4

23.0

16

45

1.3

3,710

Benin

9.1

112.6

82

45

7.1

780

Bermuda

0.1

0.1

1,294

100

..

Argentina

Australia

Bangladesh Barbados

Belize

..c

..c

5.2a

2.2a

1,940

6.7

5.4

18,900a

1.2

–5.5

14,460

5.3

5.5

39,150

1.8

0.6

1.9

–1.5

6,090a

14.6

1,610

3.5

0.7

..

..

–1.9

–1.7

Bhutan

0.7

38.4

19

36

1.6

2,130

4.1

5,570

5.6

3.8

Bolivia

10.1

1,098.6

9

67

20.4

2,020

49.3

4,890

5.2

3.5

Bosnia and Herzegovina

3.8

51.2

74

48

18.0

4,780

34.5

9,190

1.7

1.9

Botswana

2.0

581.7

4

62

15.2

7,470

29.5

14,550

5.7

4.5

196.7

8,514.9

23

85

2,107.7

10,720

2,245.8

11,420

2.7

1.8

Brazil Brunei Darussalam

0.4

5.8

77

76

12.5

31,800

19.6

49,910

2.2

0.4

Bulgaria

7.3

111.0

68

73

48.8

6,640

105.8

14,400

1.7

4.3

17.0

274.2

62

27

9.9

580

22.5

1,330

4.2

1.1

8.6

27.8

334

11

2.2

250

5.2

610

4.2

1.9

Cambodia

14.3

181.0

81

20

11.7

820

31.8

2,230

7.1

5.8

Cameroon

20.0

475.4

42

52

24.1

1,210

46.7

2,330

4.2

2.0

Canada

34.5

9,984.7

4

81

1,570.9

45,550

1,367.6

39,660

2.5

1.4

3,540

2.0

3,980

5.0

4.1

..

..

..

..

Burkina Faso Burundi

Cape Verde

0.5

4.0

124

63

1.8

Cayman Islands

0.1

0.3

236

100

..

Central African Republic

4.5

623.0

7

39

2.1

480

3.6

810

3.3

1.3

11.5

1,284.0

9

22

8.3

720

17.7

1,540

1.6

–1.0

0.2

0.2

810

31

..

..

..

..

..

17.3

756.1

23

89

212.0

12,280

282.1

16,330

6.0

5.0 8.8

Chad Channel Islands Chile China

..c

..c

1,344.1

9,600.0

144

51

6,643.2

4,940

11,270.8

8,390

9.3

Hong Kong SAR, China

7.1

1.1

6,787

100

254.6

36,010

370.2

52,350

4.9

4.8

Macao SAR, China

0.6

0.0e

19,848

100

24.7

45,460

31.0

56,950

20.7

18.1

Colombia

46.9

1,141.8

42

75

284.9

6,070

448.6

9,560

5.9

4.5

Comoros

0.8

1.9

405

28

0.6

770

0.8

1,110

2.2

–0.4

67.8

2,344.9

30

34

13.1

190

23.2

340

6.9

4.1

4.1

342.0

12

64

9.3

2,250

13.4

3,240

3.4

1.0

Congo, Dem. Rep. Congo, Rep.

20 

Surface area

World Development Indicators 2013

Front

?

User guide

World view People Environment


World view  1 Population

Costa Rica Côte d’Ivoire Croatia

Surface area

Population density

Urban population

Gross national income

millions

thousand sq. km

people per sq. km

% of total population

$ billions

Per capita $

$ billions

2011

2011

2011

2011

2011

2011

2011

Atlas method

Purchasing power parity

Gross domestic product

Per capita $

% growth

Per capita % growth 2010–11

2011

2010–11

4.7

51.1

93

65

36.1

7,640

56.1a

11,860a

4.2

2.7

20.2

322.5

63

51

22.1

1,090

34.5

1,710

–4.7

–6.7

13,540

4.4

56.6

79

58

59.6

82.7

18,780

0.0

0.3

11.3

109.9

106

75

..

..b

..

..

2.1

2.1

Curaçao

0.1

0.4

328

..

..

..c

..

..

..

..

Cyprus

1.1

9.3

121

71

23.7f

29,450 f

24.9 f

30,970 f

0.5f

0.3f

Cuba

Czech Republic

10.5

78.9

136

73

196.3

18,700

257.0

24,490

1.9

2.1

Denmark

5.6

43.1

131

87

335.1

60,160

233.5

41,920

1.1

0.7

Djibouti

0.9

23.2

39

77

1.1

1,270

2.1

2,450

5.0

3.0

Dominica

0.1

0.8

90

67

0.5

7,030

0.9a

13,000a

–0.3

–0.2

Dominican Republic

10.1

48.7

208

70

52.6

5,240

94.7a

9,420a

4.5

3.1

Ecuador

14.7

256.4

59

67

61.7

4,200

124.7

8,510

7.8

6.3

Egypt, Arab Rep.

82.5

1,001.5

83

44

214.7

2,600

504.8

6,120

1.8

0.1

6.2

21.0

301

65

21.7

3,480

41.4 a

6,640a

1.5

0.9

18.4

7.8

4.8

El Salvador Equatorial Guinea

0.7

28.1

26

40

11.3

15,670

Eritrea

5.4

117.6

54

21

2.3

430

Estonia

1.3

45.2

32

70

20.4

15,260

27.9

Ethiopia

84.7

1,104.3

85

17

31.0

370

1.4

35

41

..

48

52

3.2

25,620 580a

8.7

5.5

20,850

8.3

8.3

93.8

1,110

7.3

5.0

..

..

..

..

4.0

4,610

2.0

1.1

Faeroe Islands

0.0 g

Fiji

0.9

18.3

Finland

5.4

338.4

18

84

257.3

47,760

202.9

37,660

2.7

2.3

France

65.4

549.2

120

86

2,775.7

42,420

2,349.8

35,910

1.7

1.1

French Polynesia

0.3

4.0

75

51

..

..

..

..

..

Gabon

1.5

267.7

6

86

12.4

21.1

13,740

4.8

2.8

Gambia, The

1.8

11.3

178

–4.3

–6.9

Georgia

4.5h

69.7

79 h

..c

3.1a

3,720

..c 8,080

57

0.9

500

3.1

1,750

53h

12.8h

2,860h

24.0h

5,350h

7.0h

6.2h

Germany

81.8

357.1

235

74

3,617.7

44,230

3,287.6

40,190

3.0

3.0

Ghana

25.0

238.5

110

52

35.1

1,410

45.2

1,810

14.4

11.8

Greece

11.3

132.0

88

62

276.7

24,490

283.7

25,110

–7.1

–7.0

0.1

410.5i

0j

85

1.5

26,020

..

..

–5.4

–5.4

Grenada

0.1

0.3

309

39

0.8

7,350

1.1a

1.0

0.6

Guam

0.2

0.5

337

93

..

Guatemala

14.8

108.9

138

50

42.4

2,870

Guinea

Greenland

..c

.. 70.3a

10,350a ..

..

..

4,760a

3.9

1.3

10.2

245.9

42

36

4.4

430

10.5

1,020

3.9

1.5

Guinea-Bissau

1.5

36.1

55

44

0.9

600

1.9

1,230

5.7

3.5

Guyana

0.8

215.0

4

28

2.2

2,900

2.6 a

3,460a

4.2

4.2

10.1

27.8

367

53

7.1

700

11.9a

1,180a

5.6

4.2

7.8

112.5

69

52

15.4

1,980

29.7a

3,820a

3.6

1.6

Hungary

10.0

93.0

110

69

126.9

12,730

202.5

20,310

1.7

2.0

Iceland

0.3

103.0

3

94

11.1

34,820

9.9

31,020

2.6

2.2

Haiti Honduras

India

1,241.5

3,287.3

418

31

1,766.2

1,420

4,524.6

3,640

6.3

4.9

242.3

1,904.6

134

51

712.7

2,940

1,091.4

4,500

6.5

5.4

Iran, Islamic Rep.

74.8

1,745.2

46

69

330.4

4,520

835.5

11,420

..

..

Iraq

33.0

435.2

76

67

87.0

2,640

123.5

3,750

9.9

6.8

Ireland

4.6

70.3

66

62

179.2

39,150

153.4

33,520

0.7

–1.5

Isle of Man

0.1

0.6

146

51

..

..

..

..

..

Israel

7.8

22.1

359

92

224.7

210.5

27,110

4.7

2.8

Indonesia

Economy

States and markets

Global links

..c 28,930

Back

World Development Indicators 2013 21


1  World view Population

Italy Jamaica Japan Jordan

Population density

Urban population

millions

thousand sq. km

people per sq. km

% of total population

2011

Gross national income Atlas method

$ billions

Purchasing power parity

Per capita $

$ billions

Gross domestic product

Per capita $

% growth

Per capita % growth

2011

2011

2011

2011

2011

2011

2011

2010–11

2010–11

60.7

301.3

206

68

2,144.7

35,320

1,968.9

32,420

0.4

0.0

2.7

11.0

250

52

..

..

..

–0.3

..

127.8

377.9

351

91

5,739.5

44,900

4,516.3

35,330

–0.7

–1.0

..b

6.2

89.3

70

83

27.1

4,380

36.6

5,930

2.6

0.4

Kazakhstan

16.6

2,724.9

6

54

136.7

8,260

186.4

11,250

7.5

6.0

Kenya

41.6

580.4

73

24

34.1

820

71.1

Kiribati

0.1

0.8

125

44

0.2

2,030

Korea, Dem. Rep.

24.5

120.5

203

60

..

Korea, Rep.

49.8

99.9

513

83

1,039.0

Kosovo

1.8

10.9

166

..

6.3

3,510

..

Kuwait

2.8

17.8

158

98

133.8

48,900

147.0

Kyrgyz Republic

5.5

199.9

29

35

5.0

900

12.7

2,290

6.0

4.7

Lao PDR

6.3

236.8

27

34

7.1

1,130

16.2

2,580

8.0

6.5

Latvia

2.1

64.6

33

68

27.4

13,320 d

39.3

19,090

5.5

14.7

Lebanon

4.3

10.5

416

87

38.9

9,140

61.6

14,470

3.0

2.2

Lesotho

2.2

30.4

72

28

2.7

1,210

4.5

2,050

4.2

3.1

Liberia

4.1

111.4

43

48

1.4

330

2.2

540

9.4

5.9

Libya

6.4

1,759.5

4

78

77.1

12,320

Liechtenstein

0.0 g

0.2

227

14

4.9

137,070

..k 20,870

0.3a

1,710

4.4

1.6

3,300a

1.8

0.2

..

..

..

..

1,511.7

30,370

3.6

2.9

..

5.0

3.4

53,720

8.2

5.1

105.2a ..

16,800a

2.1

0.3

..

–1.2

–1.9

Lithuania

3.0

65.3

48

67

39.3

12,980 d

62.9

20,760

5.9

14.8

Luxembourg

0.5

2.6

200

85

40.1

77,390

33.2

64,110

1.7

–0.6

Macedonia, FYR

2.1

25.7

82

59

9.9

4,810

23.5

11,370

2.8

2.7

21.3

587.0

37

33

9.1

430

20.2

950

1.0

–1.9

Madagascar Malawi

15.4

118.5

163

16

5.6

360

13.4

870

4.3

1.1

Malaysia

28.9

330.8

88

73

253.0

8,770

451.7

15,650

5.1

3.4

0.3

0.3

1,067

41

1.8

5,720

2.4

7,430

7.5

6.1

15.8

1,240.2

13

35

9.7

610

16.8

1,060

2.7

–0.3

Maldives Mali Malta

0.4

0.3

1,299

95

7.7

18,620

10.2

24,480

2.1

2.2

Marshall Islands

0.1

0.2

305

72

0.2

3,910

..

..

5.0

3.5

Mauritania

3.5

1,030.7

3

42

3.6

1,030l

8.9

2,530

4.0

1.6

Mauritius

1.3

2.0

634

42

10.3

8,040

18.4

14,330

4.1

3.7

114.8

1,964.4

59

78

1,081.8

9,420

1,766.4

15,390

3.9

2.7

Micronesia, Fed. Sts.

0.1

0.7

159

23

0.3

2,860

0.4 a

3,580a

2.1

1.6

Moldova

3.6m

1,980m

13.0m

3,640m

Monaco

0.0 g

Mongolia

2.8

1,564.1

Montenegro

0.6

13.8

32.3

446.6

72

Mozambique

23.9

799.4

Myanmar

48.3

676.6

2.3

824.3

Nepal

30.5

147.2

213

17

16.6

540

Netherlands

16.7

41.5

495

83

829.0

49,660

Mexico

Morocco

Namibia

33.9 0.0e

124m

48m

17,714

7.1m

100

6.5

183,150

..

2

69

6.5

2,310

47

63

4.5

7,140

57

97.6n

2,970n

160.1n

30

31

11.1

460

74

33

..

3

38

10.9

..k 4,700

..c

New Caledonia

0.3

18.6

14

62

..

New Zealand

4.4

267.7

17

86

127.3

29,140

Nicaragua Niger

22 

Surface area

World Development Indicators 2013

5.9

130.4

49

58

8.9

1,510

16.1

1,267.0

13

18

5.8

360

Front

?

User guide

6.4m

6.5m

..

–2.6

–2.7

12.0

4,290

17.5

15.7

8.7

13,700

3.2

3.1

4,880n

4.5n

3.5n

22.9

960

7.1

4.7

..

..

..

..

15.4

6,610

4.8

3.0

38.4

1,260

3.9

2.1

720.3

43,150

1.0

0.5

..

..

..

..

126.3

28,930

1.0

0.1

21.9a

3,730a

5.1

3.6

11.6

720

2.3

–1.2

World view People Environment


World view  1 Population

Surface area

Population density

Urban population

Gross national income

millions

thousand sq. km

people per sq. km

% of total population

$ billions

2011

2011

2011

2011

Atlas method

Purchasing power parity

Gross domestic product

Per capita $

$ billions

Per capita $

% growth

Per capita % growth

2011

2011

2011

2011

2010–11

2010–11

162.5

923.8

178

50

207.3

1,280

372.8

2,290

7.4

4.7

Northern Mariana Islands

0.1

0.5

133

92

..

..

..

..

..

Norway

5.0

323.8

16

79

440.2

88,870

304.4

61,450

1.4

0.1

2.8

309.5

9

73

53.6

19,260

71.6

25,720

5.5

3.1

176.7

796.1

229

36

198.0

1,120

507.2

2,870

3.0

1.1

Nigeria

Oman Pakistan

..c

Palau

0.0 g

0.5

45

84

0.1

6,510

0.2a

11,080a

5.8

5.1

Panama

3.6

75.4

48

75

26.7

7,470

51.8a

14,510a

10.6

8.9 6.6

Papua New Guinea

7.0

462.8

16

13

10.4

1,480

18.0a

2,570a

9.0

Paraguay

6.6

406.8

17

62

19.8

3,020

35.4

5,390

6.9

5.0

29.4

1,285.2

23

77

151.4

5,150

277.6

9,440

6.8

5.6

Philippines

94.9

300.0

318

49

209.7

2,210

393.0

4,140

3.9

2.2

Poland

38.5

312.7

127

61

477.0

12,380o

780.8

20,260

4.3

3.4

Portugal

10.6

92.1

115

61

225.6

21,370

259.9

24,620

–1.7

–0.9

Peru

Puerto Rico

3.7

8.9

418

99

61.6

16,560

..

..

–2.1

–1.6

Qatar

1.9

11.6

161

99

150.4

80,440

161.6

86,440

18.8

11.7

Romania

21.4

238.4

93

53

174.0

8,140

337.4

15,780

2.5

2.7

143.0

17,098.2

9

74

1,522.3

10,650

2,917.7

20,410

4.3

3.9

Rwanda

10.9

26.3

444

19

6.2

570

13.9

1,270

8.3

5.1

Samoa

0.2

2.8

65

20

0.6

3,160

4,270a

2.0

1.6

San Marino

0.0 g

0.1

529

94

..

..

..

..

..

São Tomé and Príncipe

0.2

1.0

176

63

0.2

1,350

0.4

2,080

4.9

3.0

Russian Federation

0.8a

..c

Saudi Arabia

28.1

2,149.7p

13

82

500.5

17,820

693.7

24,700

6.8

4.4

Senegal

12.8

196.7

66

43

13.7

1,070

24.8

1,940

2.6

–0.1

Serbia

7.3

88.4

83

56

41.3

5,690

83.8

Seychelles

0.1

0.5

187

54

1.0

11,270

Sierra Leone

6.0

71.7

84

39

2.8

Singapore

5.2

0.7

7,405

100

222.6

Sint Maarten

0.0 g

0.0e

1,077

..

..

Slovak Republic

5.4

49.0

112

55

87.4

Slovenia

2.1

20.3

102

50

Solomon Islands

0.6

28.9

20

21

Somalia

9.6

637.7

15

38

..

50.6

1,219.1

42

62

352.0

South Africa

11,550

2.0

2.5

2.3a

26,280a

5.0

5.6

460

6.8

1,140

6.0

3.7

42,930

307.8

59,380

4.9

2.7

..

..

..

..

16,190

120.4

22,300

3.3

4.0

48.5

23,600

54.4

26,500

–0.2

–0.4

0.6

1,110

9.0

6.2

..c

..k 6,960

2,350a

..

..

..

..

542.0

10,710

3.1

1.9

South Sudan

10.3p

644.3

..

18

..

..

..

1.9

–1.7

Spain

46.2

505.4

93

77

1,428.3

30,930

1,451.7

31,440

0.4

0.2

Sri Lanka

20.9

65.6

333

15

53.8

2,580

115.2

5,520

8.3

7.1

St. Kitts and Nevis

0.1

0.3

204

32

0.7

12,610

0.9a

16,470a

2.1

0.9

St. Lucia

0.2

0.6

289

18

1.2

6,820

2.0a

11,220a

1.3

0.1

g

St. Martin

0.0

St. Vincent and Grenadines

0.1 34.3p,r

Sudan

..q

1.3a

c

0.1

563

..

..

..

..

..

..

0.4

280

49

0.7

6,070

1.1a

..

10,440a

0.1

0.1

1,861.5r

18

33

58.3u

1,310u

94.7u

2,120u

4.7u

2.2u

a

a

Suriname

0.5

163.8

3

70

4.1

7,840

4.1

Swaziland

1.1

17.4

62

21

3.7

3,470

6.5

Sweden

9.4

450.3

23

85

502.5

53,170

398.9

42,210

3.9

3.1

Switzerland

7.9

41.3

198

74

604.1

76,350

415.6

52,530

1.9

0.8

20.8

185.2

113

56

67.9

2,750

104.0

5,080

..

..

7.0

142.6

50

27

6.1

870

16.0

2,300

7.4

5.9

Syrian Arab Republic Tajikistan

Economy

States and markets

Global links

Back

7,730

6,110

4.7

3.7

1.3

0.1

World Development Indicators 2013 23


1  World view Population

Surface area

Population density

Urban population

Gross national income

millions

thousand sq. km

people per sq. km

% of total population

$ billions

Per capita $

$ billions

2011

2011

2011

2011

2011

2011

2011

Atlas method

Purchasing power parity

Gross domestic product

Per capita $

% growth

Per capita % growth

2011

2010–11

2010–11

6.4v

3.3v –0.5

Tanzania

46.2

947.3

52

27

24.2 v

540 v

67.1v

1,500 v

Thailand

581.4

69.5

513.1

136

34

308.3

4,440

Timor-Leste

1.2

14.9

79

28

3.1

2,730

Togo

6.2

56.8

113

38

3.5

570

Tonga

0.1

0.8

145

24

0.4

3,820

0.5a

5,000a

4.9

4.5

Trinidad and Tobago

1.3

5.1

262

14

21.3

15,840

32.7a

24,350a

–4.1

–4.4

96.0

8,990

–2.0

–3.1

1,247.3

16,940

8.5

7.2

14.7

13.3

4,020 d

Tunisia

10.7

163.6

69

66

42.9

Turkey

73.6

783.6

96

71

766.6

10,410

5.1

488.1

11

49

24.5

4,800

Turks and Caicos Islands

0.0 g

1.0

41

94

..

Tuvalu

0.0 g

0.0e

328

51

0.0

Uganda

34.5

241.6

173

16

17.5

Ukraine

45.7

603.6

79

69

142.9

7.9

83.6

94

84

321.7

40,760

Turkmenistan

United Arab Emirates United Kingdom United States Uruguay

..c

8,360

0.1

5.9a

5,200a

10.6

7.5

6.4

1,040

4.9

2.7

44.3a

8,690a

..

..

..

..

..

..

1.2

1.0

510

45.3

1,310

6.7

3.3

3,130

321.9

7,040

5.2

5.6

377.9

47,890

4.9

–0.1

4,950

62.7

243.6

259

80

2,370.4

37,780

2,255.9

35,950

0.8

0.0

311.6

9,831.5

34

82

15,148.2

48,620

15,211.3

48,820

1.7

1.0

49.3

14,640

5.7

5.3

3.4

176.2

19

93

40.0

11,860

29.3

447.4

69

36

44.2

1,510

100.3a

3,420a

8.3

5.4

0.2

12.2

20

25

0.7

2,730

1.1a

4,330a

1.4

–1.0

Venezuela, RB

29.3

912.1

33

94

346.1

11,820

363.9

12,430

4.2

2.6

Vietnam

87.8

331.1

283

31

111.1

1,270

285.5

3,250

5.9

4.8 ..

Uzbekistan Vanuatu

Virgin Islands (U.S.)

0.1

0.4

313

95

..

..c

..

..

..

West Bank and Gaza

3.9

6.0

652

74

..

..q

..

..

..

..

24.8

528.0

47

32

26.4

1,070

53.7

2,170

–10.5

–13.2 2.1

Yemen, Rep. Zambia

13.5

752.6

18

39

15.7

1,160

20.1

1,490

6.5

Zimbabwe

12.8

390.8

33

39

8.4

660

..

..

9.4

7.8

54 w

52 w

2.7 w

1.6 w

World Low income Middle income

6,974.2 s

134,269.2 s

816.8

16,582.1

51

28

466.0

5,022.4

81,875.7

63

50

20,835.4

66,354.3

t

9,514 w

80,624.2 t

11,560 w

571

1,125.4

1,378

6.0

3.7

4,149

36,311.9

7,230

6.3

5.2

Lower middle income

2,532.7

20,841.9

126

39

4,488.5

1,772

9,719.0

3,837

5.5

3.9

Upper middle income

2,489.7

61,033.8

42

61

16,340.5

6,563

26,646.2

10,703

6.6

5.9

Low & middle income

5,839.2

98,457.7

61

47

21,324.4

3,652

37,436.4

6,411

6.3

5.0

East Asia & Pacific

1,974.2

16,301.7

125

49

8,387.3

4,248

14,344.6

7,266

8.3

7.6

408.1

23,613.7

18

65

3,156.6

7,734

5,845.7

14,323

5.9

5.4

Latin America & Carib.

589.0

20,393.6

29

79

5,050.3

8,574

6,822.0

11,582

4.7

3.6

Middle East & N. Africa

336.5

8,775.4

39

59

1,279.5

3,866

2,619.2

8,052

0.2

2.4

1,656.5

5,131.1

347

31

2,174.5

1,313

5,523.5

3,335

6.1

4.6 2.1

Europe & Central Asia

South Asia Sub-­Saharan Africa High income Euro area

874.8

24,242.3

37

37

1,100.8

1,258

1,946.2

2,225

4.7

1,135.0

35,811.5

33

81

45,242.5

39,861

43,724.5

38,523

1.5

0.9

332.9

2,628.4

131

76

12,871.5

38,661

11,735.7

35,250

1.5

1.2

a. Based on regression; others are extrapolated from the 2005 International Comparison Program benchmark estimates. b. Estimated to be upper middle income ($4,036–$12,475). c. Estimated to be high income ($12,476 or more). d. Included in the aggregates for upper middle-income economies based on earlier data. e. Greater than 0 but less than 50. f. Data are for the area controlled by the government of Cyprus. g. Greater than 0 but less than 50,000. h. Excludes Abkhazia and South Ossetia. i. Refers to area free from ice. j. Greater than 0 but less than 0.5. k. Estimated to be low income ($1,025 or less). l. Included in the aggregates for low-income economies based on earlier data. m. Excludes Transnistria. n. Includes Former Spanish Sahara. o. Included in the aggregates for high-income economies based on earlier data. p. Provisional estimate. q. Estimated to be lower middle income ($1,026–$4,035). r. Excludes South Sudan. s. Sum of available data (see Statistical methods). t. Missing data are imputed (see Statistical methods). u. Excludes South Sudan after July 9, 2011. v. Covers mainland Tanzania only. w. Weighted average (see Statistical methods).

24 

World Development Indicators 2013

Front

?

User guide

World view People Environment


World view  1 About the data Population, land area, income (as measured by gross national

area, which excludes bodies of water, and from gross area, which

income, GNI), and output (as measured by gross domestic product,

may include offshore territorial waters. Land area is particularly

GDP) are basic measures of the size of an economy. They also pro-

important for understanding an economy’s agricultural capacity and

vide a broad indication of actual and potential resources and are

the environmental effects of human activity. Innovations in satellite

therefore used throughout World Development Indicators to normal-

mapping and computer databases have resulted in more precise

ize other indicators.

measurements of land and water areas.

Population

Urban population

Population estimates are usually based on national population cen-

There is no consistent and universally accepted standard for

suses. Estimates for the years before and after the census are

distinguishing urban from rural areas, in part because of the

interpolations or extrapolations based on demographic models.

wide variety of situations across countries. Most countries use

Errors and undercounting occur even in high-income countries; in

an urban classification related to the size or characteristics

developing countries errors may be substantial because of limits

of settlements. Some define urban areas based on the pres-

in the transport, communications, and other resources required to

ence of certain infrastructure and services. And other countries

conduct and analyze a full census.

designate urban areas based on administrative arrangements.

The quality and reliability of official demographic data are also

Because the estimates in the table are based on national defi-

affected by public trust in the government, government commit-

nitions of what constitutes a city or metropolitan area, cross-

ment to full and accurate enumeration, confidentiality and pro-

country comparisons should be made with caution. To estimate

tection against misuse of census data, and census agencies’

urban populations, ratios of urban to total population obtained

independence from political influence. Moreover, comparability of

from the United Nations were applied to the World Bank’s esti-

population indicators is limited by differences in the concepts,

mates of total population.

definitions, collection procedures, and estimation methods used by national statistical agencies and other organizations that col-

Size of the economy

lect the data.

GNI measures total domestic and foreign value added claimed by

Of the 214 economies in the table, 180 (about 86 percent) con-

residents. GNI comprises GDP plus net receipts of primary income

ducted a census during the 2000 census round (1995–2004). As

(compensation of employees and property income) from nonresi-

of January 2012, 141 countries have completed a census for the

dent sources. GDP is the sum of gross value added by all resident

2010 census round (2005–14). The currentness of a census and

producers in the economy plus any product taxes (less subsidies)

the availability of complementary data from surveys or registration

not included in the valuation of output. GNI is calculated without

systems are important indicators of demographic data quality. See

deducting for depreciation of fabricated assets or for depletion and

Primary data documentation for the most recent census or survey

degradation of natural resources. Value added is the net output of

year and for the completeness of registration. Some European coun-

an industry after adding up all outputs and subtracting intermedi-

tries’ registration systems offer complete information on population

ate inputs. The industrial origin of value added is determined by

in the absence of a census.

the International Standard Industrial Classification revision 3. The

Current population estimates for developing countries that

World Bank uses GNI per capita in U.S. dollars to classify countries

lack recent census data and pre- and post-census estimates for

for analytical purposes and to determine borrowing eligibility. For

countries with census data are provided by the United Nations

definitions of the income groups in World Development Indicators,

Population Division and other agencies. The cohort compo-

see User guide.

nent method—a standard method for estimating and projecting

When calculating GNI in U.S. dollars from GNI reported in national

­p opulation—requires fertility, mortality, and net migration data,

currencies, the World Bank follows the World Bank Atlas conversion

often collected from sample surveys, which can be small or limited

method, using a three-year average of exchange rates to smooth

in coverage. Population estimates are from demographic modeling

the effects of transitory fluctuations in exchange rates. (For fur-

and so are susceptible to biases and errors from shortcomings in

ther discussion of the World Bank Atlas method, see Statistical

the model and in the data. Because the five-year age group is the

methods.)

cohort unit and five-year period data are used, interpolations to

Because exchange rates do not always reflect differences in price

obtain annual data or single age structure may not reflect actual

levels between countries, the table also converts GNI and GNI per

events or age composition.

capita estimates into international dollars using purchasing power parity (PPP) rates. PPP rates provide a standard measure allowing

Surface area

comparison of real levels of expenditure between countries, just

The surface area of an economy includes inland bodies of water

as conventional price indexes allow comparison of real values over

and some coastal waterways. Surface area thus differs from land

time.

Economy

States and markets

Global links

Back

World Development Indicators 2013 25


1  World view PPP rates are calculated by simultaneously comparing the prices

Data sources

of similar goods and services among a large number of countries.

The World Bank’s population estimates are compiled and produced

In the most recent round of price surveys conducted by the Interna-

by its Development Data Group in consultation with its Human Devel-

tional Comparison Program (ICP) in 2005, 146 countries and ter-

opment Network, operational staff, and country offices. The United

ritories participated, including China for the first time, India for the

Nations Population Division (2011) is a source of the demographic

first time since 1985, and almost all African countries. The PPP

data for more than half the countries, most of them developing

conversion factors presented in the table come from three sources.

countries. Other important sources are census reports and other

For 47 high- and upper middle-income countries conversion fac-

statistical publications from national statistical offices; household

tors are provided by Eurostat and the Organisation for Economic

surveys by national agencies, ICF International (for MEASURE DHS),

Co-operation and Development (OECD); PPP estimates for these

and the U.S. Centers for Disease Control and Prevention; Eurostat’s

countries incorporate new price data collected since 2005. For the

Demographic Statistics; the Secretariat of the Pacific Community’s

remaining 2005 ICP countries the PPP estimates are extrapolated

Statistics and Demography Programme; and the U.S. Bureau of the

from the 2005 ICP benchmark results, which account for relative

Census’s International Data Base.

price changes between each economy and the United States. For

Data on surface and land area are from the Food and Agricul-

countries that did not participate in the 2005 ICP round, the PPP

ture Organization, which gathers these data from national agen-

estimates are imputed using a statistical model. More information

cies through annual questionnaires and by analyzing the results of

on the results of the 2005 ICP is available at www.worldbank.org/

national agricultural censuses.

data/icp.

Data on urban population shares are from United Nations Popula-

Growth rates of GDP and GDP per capita are calculated using the

tion Division (2010).

least squares method and constant price data in local currency.

GNI, GNI per capita, GDP growth, and GDP per capita growth are

Constant price U.S. dollar series are used to calculate regional and

estimated by World Bank staff based on national accounts data col-

income group growth rates. The growth rates in the table are annual

lected by World Bank staff during economic missions or reported by

averages. Methods of computing growth rates are described in Sta-

national statistical offices to other international organizations such

tistical methods.

as the OECD. PPP conversion factors are estimates by Eurostat/ OECD and by World Bank staff based on data collected by the ICP.

Definitions • Population is based on the de facto definition of population, which

References

counts all residents regardless of legal status or ­citizenship—

Eurostat (Statistical Office of the European Communities). n.d. Demo-

except for refugees not permanently settled in the country of asy-

graphic Statistics. http://epp.eurostat.ec.europa.eu/portal/page/

lum, who are generally considered part of the population of their country of origin. The values shown are midyear estimates. • Surface area is a country’s total area, including areas under inland bodies of water and some coastal waterways. • Population density is midyear population divided by land area. • Urban population is

http://www.measuredhs.com. Calverton, MD. OECD (Organisation for Economic Co-operation and Development). n.d. OECD.StatExtracts database. http://stats.oecd.org/. Paris.

the midyear population of areas defined as urban in each country

UNAIDS (Joint United Nations Programme on HIV/AIDS). 2012. Global

and reported to the United Nations. • Gross national income, Atlas

Report: UNAIDS Report on the Global AIDS Epidemic 2012. www

method, is the sum of value added by all resident producers plus

.unaids.org/en/resources/publications/2012/. Geneva.

any product taxes (less subsidies) not included in the valuation

United Nations Inter-Agency Group for Child Mortality Estimation.

of output plus net receipts of primary income (compensation of

2012. Levels and Trends in Child Mortality: Report 2012. www

employees and property income) from abroad. Data are in current

.childinfo.org/files/Child_Mortality_Report_2012.pdf. New York.

U.S. dollars converted using the World Bank Atlas method (see

United Nations. 2012. The Millennium Development Goals Report

Statistical methods). • Gross national income, purchasing power

2012. New York.

parity, is GNI converted to international dollars using PPP rates. An

United Nations Population Division. 2010. World Urbanization Pros-

international dollar has the same purchasing power over GNI that

pects: The 2009 Revision. New York: United Nations, Department of

a U.S. dollar has in the United States. • Gross national income per capita is GNI divided by midyear population. • Gross domestic

Economic and Social Affairs. ———. 2011. World Population Prospects: The 2010 Revision. New

product is the sum of value added by all resident producers plus

York: United Nations, Department of Economic and Social Affairs.

any product taxes (less subsidies) not included in the valuation of

World Bank. 2011. The Changing Wealth of Nations: Measuring Sustain-

output. Growth is calculated from constant price GDP data in local currency. • Gross domestic product per capita is GDP divided by midyear population.

26 

portal/eurostat/home/. Luxembourg. ICF International. Various years. Demographic and Health Surveys.

World Development Indicators 2013

able Development for the New Millennium. Washington, DC. ———. n.d. PovcalNet online database. http://iresearch.worldbank .org/PovcalNet/index.htm

Front

?

User guide

World view People Environment


World view  1 About the Online tables dataand indicators To access the World Development Indicators online tables, use

indicator online, use the URL http://data.worldbank.org/indicator/

the URL http://wdi.worldbank.org/table/ and the table number (for

and the indicator code (for example, http://data.worldbank.org/

example, http://wdi.worldbank.org/table/1.1). To view a specific

indicator/SP.POP.TOTL).

1.1 Size of the economy

Carbon dioxide emissions per capita

Population

SP.POP.TOTL

Surface area

AG.SRF.TOTL.K2

Population density

EN.POP.DNST

Nationally protected terrestrial and marine areas Access to improved sanitation facilities

EN.ATM.CO2E.PC ER.PTD.TOTL.ZS SH.STA.ACSN ..a

Gross national income, Atlas method

NY.GNP.ATLS.CD

Individuals using the Internet

Gross national income per capita, Atlas method

NY.GNP.PCAP.CD

1.4 Millennium Development Goals: overcoming obstacles

Purchasing power parity gross national income

NY.GNP.MKTP.PP.CD

Purchasing power parity gross national income, Per capita

NY.GNP.PCAP.PP.CD

Gross domestic product

NY.GDP.MKTP.KD.ZG

Gross domestic product, Per capita

NY.GDP.PCAP.KD.ZG

1.2 Millennium Development Goals: eradicating poverty and saving lives

This table provides data on net official development assistance by donor, least developed countries’ access to high-income markets, and the Debt Initiative for Heavily Indebted Poor Countries.

1.5 Women in development Female population

SP.POP.TOTL.FE.ZS

Life expectancy at birth, Male

SP.DYN.LE00.MA.IN

Life expectancy at birth, Female

Share of poorest quintile in national consumption or income

SI.DST.FRST.20

SH.STA.ANVC.ZS SP.MTR.1519.ZS

Vulnerable employment

SL.EMP.VULN.ZS

Prevalence of malnutrition, Underweight

SH.STA.MALN.ZS

Primary completion rate

SE.PRM.CMPT.ZS

Women in wage employment in nonagricultural sector

Under-five mortality rate

SP.DYN.LE00.FE.IN

Pregnant women receiving prenatal care Teenage mothers

Ratio of girls to boys enrollments in primary and secondary education

..a

Unpaid family workers, Male

SL.EMP.INSV.FE.ZS SL.FAM.WORK.MA.ZS

SE.ENR.PRSC.FM.ZS

Unpaid family workers, Female

SL.FAM.WORK.FE.ZS

SH.DYN.MORT

Female part-time employment

SL.TLF.PART.TL.FE.ZS

1.3 Millennium Development Goals: protecting our

Female legislators, senior officials, and managers

common environment

Women in parliaments

SG.GEN.PARL.ZS

Female-headed households

SP.HOU.FEMA.ZS

Maternal mortality ratio, Modeled estimate

SH.STA.MMRT

Contraceptive prevalence rate

SP.DYN.CONU.ZS

HIV prevalence

SH.DYN.AIDS.ZS

Incidence of tuberculosis

Economy

SH.TBS.INCD

States and markets

SG.GEN.LSOM.ZS

Data disaggregated by sex are available in the World Development Indicators database. a. Available online only as part of the table, not as an individual indicator.

Global links

Back

World Development Indicators 2013 27


Poverty rates Population below international poverty linesa

International poverty line in local currency

Poverty gap at $2 a day %

Population Poverty gap Population below at $1.25 below $1.25 a day a day $2 a day % % %

Poverty gap at $2 a day %

$2 a day

2005

2005

Survey year b

120.8

2005

<2

<0.5

7.9

1.5

2008

<2

<0.5

4.3

0.9

1988

7.6

1.2

24.6

6.7

1995

6.8

1.4

23.6

6.5

..

..

..

..

2000

54.3

29.9

70.2

42.4

2009d,e

2.0

1.2

3.4

1.7

2010 d,e

<2

0.7

<2

0.9 4.0

Survey year b

Albania

75.5

Algeria

48.4 c

Angola

88.1

141.0

1.7

2.7

245.2

392.4

2008

<2

<0.5

12.4

2.3

2010

2.5

<0.5

19.9

2,170.9

3,473.5

2001

6.3

1.1

27.1

6.8

2008

<2

<0.5

2.8

0.6

31.9

51.0

2005

50.5

14.2

80.3

34.3

2010

43.3

11.2

76.5

30.4

949.5

1,519.2

2008

<2

<0.5

<2

<0.5

2010

<2

<0.5

<2

<0.5

1998f

11.3

4.7

26.3

10.0

1999 f

12.2

5.5

22.0

9.9

..

..

..

..

2003

47.3

15.7

75.3

33.5

Argentina Armenia Azerbaijan Bangladesh Belarus Belize Benin

1.8 c

77.5c

2.9c

344.0

550.4

Bhutan

23.1

36.9

2003

26.2

7.0

49.5

18.8

2007

10.2

1.8

29.8

8.5

Bolivia

3.2

5.1

2007e

13.1

6.6

24.7

10.9

2008e

15.6

8.6

24.9

13.1

Bosnia and Herzegovina

1.1

1.7

2004

<2

<0.5

<2

<0.5

2007

<2

<0.5

<2

<0.5

Botswana

4.2

6.8

1986

35.6

13.8

54.7

25.8

1994

31.2

11.0

49.4

22.3

Brazil

2.0

3.1

2008f

6.0

3.4

11.3

5.3

2009 f

6.1

3.6

10.8

5.4

Bulgaria

0.9

1.5

2003

<2

<0.5

<2

<0.5

2007

<2

<0.5

<2

<0.5

Burkina Faso

303.0

484.8

2003

56.5

20.3

81.2

39.3

2009

44.6

14.7

72.6

31.7

Burundi

558.8

894.1

1998

86.4

47.3

95.4

64.1

2006

81.3

36.4

93.5

56.1

Cambodia

2,019.1

3,230.6

2008

22.8

4.9

53.3

17.4

2009

18.6

3.6

49.5

15.1

Cameroon

368.1

589.0

2001

10.8

2.3

32.5

9.5

2007

9.6

1.2

30.4

8.2

97.7

156.3

..

..

..

..

2002

21.0

6.1

40.9

15.2

62.4

28.3

81.9

45.3

2008

62.8

31.3

80.1

46.8

..

..

..

..

2003

61.9

25.6

83.3

43.9 1.2

Cape Verde Central African Republic

384.3

614.9

Chad

409.5

655.1

Chile

484.2

774.7

China

5.1g

2003

8.2g

2006f

<2

0.5

3.2

1.1

2009 f

<2

0.7

2.7

2008h

13.1

3.2

29.8

10.1

2009h

11.8

2.8

27.2

9.1

2009 f

9.7

4.7

18.5

8.2

2010 f

8.2

3.8

15.8

6.8 34.2

Colombia

1,489.7

2,383.5

Comoros

368.0

588.8

..

..

..

..

2004

46.1

20.8

65.0

Congo, Dem. Rep.

395.3

632.5

..

..

..

..

2006

87.7

52.8

95.2

67.6

Congo, Rep.

469.5

751.1

..

..

..

..

2005

54.1

22.8

74.4

38.8

Costa Rica

348.7c

557.9c

2008f

2.4

1.5

5.0

2.3

2009 f

3.1

1.8

6.0

2.7

Côte d’Ivoire

407.3

651.6

2002

23.3

6.8

46.8

17.6

2008

23.8

7.5

46.3

17.8

Croatia Czech Republic Djibouti

5.6

8.9

2004

<2

<0.5

<2

<0.5

2008

<2

<0.5

<2

<0.5

19.0

30.4

1993e

<2

<0.5

<2

<0.5

1996e

<2

<0.5

<2

<0.5

134.8

215.6

..

..

..

..

2002

18.8

5.3

41.2

14.6 2.4

25.5c

40.8 c

2009 f

3.0

0.7

10.0

2.7

2010 f

2.2

<0.5

9.9

Ecuador

0.6

1.0

2009 f

6.4

2.9

13.5

5.5

2010 f

4.6

2.1

10.6

4.1

Egypt, Arab Rep.

2.5

4.0

2005

2.0

<0.5

18.5

3.5

2008

<2

<0.5

15.4

2.8

El Salvador

6.0 c

9.6c

2008f

5.4

1.9

14.0

4.8

2009 f

9.0

4.4

16.9

7.6

2003

<2

<0.5

2.6

<0.5

2004

<2

<0.5

<2

0.5

Dominican Republic

Estonia

11.0

17.7

Ethiopia

3.4

5.5

2005

39.0

9.6

77.6

28.9

2011

30.7

8.2

66.0

23.6

Fiji

1.9

3.1

2003

29.2

11.3

48.7

21.8

2009

5.9

1.1

22.9

6.0

554.7

887.5

..

..

..

..

2005

4.8

0.9

19.6

5.0

12.9

20.7

1998

65.6

33.8

81.2

49.1

2003

29.8

9.8

55.9

24.4

1.0

1.6

2008

15.3

4.6

32.2

11.7

2010

18.0

5.8

35.6

13.7

5,594.8

8,951.6

1998

39.1

14.4

63.3

28.5

2006

28.6

9.9

51.8

21.3

2004f

24.4

13.2

39.2

20.2

2006f

13.5

4.7

26.3

10.5

2003

56.3

21.3

80.8

39.7

2007

43.3

15.0

69.6

31.0

Gabon Gambia, The Georgia Ghana Guatemala Guinea

28 

Population Poverty gap Population below at $1.25 below $1.25 a day a day $2 a day % % %

$1.25 a day

World Development Indicators 2013

5.7c 1,849.5

9.1c 2,959.1

Front

?

User guide

World view People Environment


Poverty rates Population below international poverty linesa

International poverty line in local currency

Population Poverty gap Population below at $1.25 below $1.25 a day a day $2 a day % % %

Poverty gap at $2 a day %

Population Poverty gap Population below at $1.25 below $1.25 a day a day $2 a day % % %

Poverty gap at $2 a day %

$1.25 a day

$2 a day

2005

2005

Guinea-Bissau

355.3

568.6

1993

52.1

20.6

75.7

37.4

2002

48.9

16.6

78.0

Guyana

131.5c

210.3c

1993e

6.9

1.5

17.1

5.4

1998e

8.7

2.8

18.0

6.7

Haiti

24.2c

38.7c

..

..

..

..

2001

61.7

32.3

77.5

46.7

Honduras

12.1c

19.3c

2008f

21.4

11.8

32.6

17.5

2009 f

17.9

9.4

29.8

14.9

2004

<2

<0.5

<2

<0.5

2007

<2

<0.5

<2

<0.5

Hungary

171.9

275.0

Survey year b

Survey year b

34.9

19.5i

31.2i

2005h

41.6

10.5

75.6

29.5

2010h

32.7

7.5

68.7

24.5

Indonesia

5,241.0i

8,385.7i

2009h

20.4

4.1

52.7

16.5

2010h

18.1

3.3

46.1

14.3

Iran, Islamic Rep.

3,393.5

5,429.6

1998

<2

<0.5

8.3

1.8

2005

<2

<0.5

8.0

1.8

799.8

1,279.7

..

..

..

..

2007

2.8

<0.5

21.4

4.4

2004

<2

<0.5

5.4

0.8

India

Iraq Jamaica Jordan

54.2c

86.7c

2002

<2

<0.5

8.5

1.5

0.6

1.0

2008

<2

<0.5

2.1

<0.5

2010

<2

<0.5

<2

<0.5

Kazakhstan

81.2

129.9

2008

<2

<0.5

<2

<0.5

2009

<2

<0.5

<2

<0.5

Kenya

40.9

65.4

1997

19.6

4.6

42.7

14.7

2005

43.4

16.9

67.2

31.8

Kyrgyz Republic

16.2

26.0

2009

6.2

1.4

21.7

6.0

2010

6.7

1.5

22.9

6.4

4,677.0

7,483.2

2002

44.0

12.1

76.9

31.1

2008

33.9

9.0

66.0

24.8

Lao PDR Latvia

0.4

0.7

2008

<2

<0.5

<2

<0.5

2009

<2

<0.5

<2

<0.5

Lesotho

4.3

6.9

1994

46.2

25.6

59.7

36.1

2003

43.4

20.8

62.3

33.1

..

..

..

..

2007

83.8

40.9

94.9

59.6

<2

<0.5

<2

0.5

2008

<2

<0.5

<2

<0.5

Liberia

0.6

1.0

Lithuania

2.1

3.3

2004

Macedonia, FYR Madagascar Malawi

29.5

47.2

2009

<2

<0.5

5.9

0.9

2010

<2

<0.5

6.9

1.2

945.5

1,512.8

2005

67.8

26.5

89.6

46.9

2010

81.3

43.3

92.6

60.1

1998

83.1

46.0

93.5

62.3

2004

73.9

32.3

90.5

51.8

<2

<0.5

2.9

<0.5

2009e

<2

<0.5

2.3

<0.5

71.2

113.8

Malaysia

2.6

4.2

Maldives

358.3

573.5

..

..

..

..

2004

<2

<0.5

12.2

2.5

Mali

362.1

579.4

2006

51.4

18.8

77.1

36.5

2010

50.4

16.4

78.7

35.2

Mauritania

17.7

2007e

157.1

251.3

2004

25.4

7.0

52.6

19.2

2008

23.4

6.8

47.7

Mexico

9.6

15.3

2008

<2

<0.5

5.2

1.3

2010

<2

<0.5

4.5

1.0

Micronesia, Fed. Sts.

0.8 c

..

..

..

..

31.2

16.3

44.7

24.5

Moldova

6.0

9.7

2009

<2

<0.5

7.1

1.2

2010

<2

<0.5

4.4

0.7

Montenegro

0.6

1.0

2008

<2

<0.5

<2

<0.5

2010

<2

<0.5

<2

<0.5

6.9

11.0

2001

6.3

0.9

24.3

6.3

2007

2.5

0.5

14.0

3.2

14,532.1 23,251.4

2003

74.7

35.4

90.0

53.6

2008

59.6

25.1

81.8

42.9

Morocco Mozambique Namibia Nepal Nicaragua Niger

1.3c

2000 d

6.3

10.1

1993e

49.1

24.6

62.2

36.5

2004 e

31.9

9.5

51.1

21.8

33.1

52.9

2003

53.1

18.4

77.3

36.6

2010

24.8

5.6

57.3

19.0

14.6c

2001e

14.4

3.7

34.4

11.5

2005e

11.9

2.4

31.7

9.6

2005

50.2

18.3

75.3

35.6

2008

43.6

12.4

75.2

30.8

9.1c 334.2

534.7

Nigeria

98.2

157.2

2004

63.1

28.7

83.1

45.9

2010

68.0

33.7

84.5

50.2

Pakistan

25.9

41.4

2006

22.6

4.1

61.0

18.8

2008

21.0

3.5

60.2

17.9

2009 f

5.9

1.8

14.6

4.9

2010 f

6.6

2.1

13.8

5.1

..

..

..

..

1996

35.8

12.3

57.4

25.5

Panama

0.8 c

1.2c

Papua New Guinea

2.1c

3.4 c

Paraguay Peru Philippines

4,255.6

2009 f

7.6

3.2

14.2

6.0

2010 f

7.2

3.0

13.2

5.7

2.1

3.3

2009 f

5.5

1.6

14.0

4.6

2010 f

4.9

1.3

12.7

4.1

2,659.7 30.2

48.4

2006

22.6

5.5

45.0

16.4

2009

18.4

3.7

41.5

13.8

Poland

2.7

4.3

2009

<2

<0.5

<2

<0.5

2010

<2

<0.5

<2

<0.5

Romania

2.1

3.4

2009

<2

<0.5

<2

0.5

2010

<2

<0.5

<2

<0.5

16.7

26.8

2008

<2

<0.5

<2

<0.5

2009

<2

<0.5

<2

<0.5

295.9

473.5

2006

72.1

34.8

87.4

52.2

2011

63.2

26.6

82.4

44.6

Russian Federation Rwanda

Economy

States and markets

Global links

Back

World Development Indicators 2013 29


Poverty rates Population below international poverty linesa

International poverty line in local currency

$1.25 a day

$2 a day

2005

2005

São Tomé and Príncipe Senegal Serbia Seychelles Sierra Leone Slovak Republic Slovenia South Africa Sri Lanka St. Lucia Sudan

Survey year b

Population Poverty gap Population below at $1.25 below $1.25 a day a day $2 a day % % %

7,953.9 12,726.3 372.8

596.5

42.9

68.6

5.6c

9.0 c

Poverty gap at $2 a day %

Survey year b

Population Poverty gap Population below at $1.25 below $1.25 a day a day $2 a day % % %

Poverty gap at $2 a day %

..

..

..

..

2001

28.2

7.9

54.2

20.6

2005

33.5

10.8

60.4

24.7

2011

29.6

9.1

55.2

21.9

2009

<2

<0.5

<2

<0.5

2010

<2

<0.5

<2

<0.5

2000

<2

<0.5

<2

<0.5

2007

<2

<0.5

<2

<0.5

1990

62.8

44.8

75.0

54.0

2003

53.4

20.3

76.1

37.5

<2

<0.5

<2

<0.5

2009e

<2

<0.5

<2

<0.5

1,745.3

2,792.4

23.5

37.7

198.2

317.2

2003

<2

<0.5

<2

<0.5

2004

<2

<0.5

<2

<0.5

5.7

9.1

2006

17.4

3.3

35.7

12.3

2009

13.8

2.3

31.3

10.2

50.0

80.1

2007

7.0

1.0

29.1

7.4

2010

4.1

0.7

23.9

5.4

..

..

..

..

1995

20.9

7.2

40.6

15.5

..

..

..

..

2009

19.8

5.5

44.1

15.4

..

..

..

..

1999

15.5

5.9

27.2

11.7

2001

62.9

29.4

81.0

45.8

2010

40.6

16.0

60.4

29.3 3.3

2.4 c 154.4

2008e

3.8 c 247.0

Suriname

2.3c

3.7c

Swaziland

4.7

7.5

30.8

49.3

..

..

..

..

2004

<2

<0.5

16.9

1.2

1.9

2007

14.7

4.4

37.0

12.2

2009

6.6

1.2

27.7

7.0

Tanzania

603.1

964.9

2000

84.6

41.6

95.3

60.3

2007

67.9

28.1

87.9

47.5

Thailand

21.8

34.9

2009j

<2

<0.5

4.6

0.8

2010j

<2

<0.5

4.1

0.7

352.8

564.5

2006

38.7

11.4

69.3

27.9

2011

28.2

8.8

52.7

20.9 3.9

Syrian Arab Republic Tajikistan

Togo Trinidad and Tobago

5.8 c

9.2c

1988e

<2

<0.5

8.6

1.9

1992e

4.2

1.1

13.5

Tunisia

0.9

1.4

2005

<2

<0.5

8.1

1.8

2010

<2

<0.5

4.3

1.1

Turkey

1.3

2.0

2008

<2

<0.5

4.2

0.7

2010

<2

<0.5

4.7

1.4 18.4

5,961.1c

9,537.7c

1993e

63.5

25.8

85.7

44.9

1998e

24.8

7.0

49.7

Uganda

930.8

1,489.2

2006

51.5

19.1

75.6

36.4

2009

38.0

12.2

64.7

27.4

Ukraine

2.1

3.4

2009

<2

<0.5

<2

<0.5

2010

<2

<0.5

<2

<0.5

Uruguay

19.1

30.6

2009 f

<2

<0.5

<2

<0.5

2010 f

<2

<0.5

<2

<0.5

13.4

8.2

21.9

11.6

2006f

6.6

3.7

12.9

5.9

21.4

5.3

48.1

16.3

2008

16.9

3.8

43.4

13.5

Turkmenistan

Venezuela, RB

1,563.9

2,502.2

2005f

Vietnam

7,399.9 11,839.8

2006

West Bank and Gaza Yemen, Rep. Zambia

2.7c

4.3c

2007

<2

<0.5

2.5

0.5

2009

<2

<0.5

<2

<0.5

113.8

182.1

1998

12.9

3.0

36.4

11.1

2005

17.5

4.2

46.6

14.8

3,537.9

5,660.7

2004

64.3

32.8

81.5

48.3

2006

68.5

37.0

82.6

51.8

a. Based on nominal per capita consumption averages and distributions estimated parametrically from grouped household survey data, unless otherwise noted. b. Refers to the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which most of the data were collected. c. Based on purchasing power parity (PPP) dollars imputed using regression. d. Covers urban areas only. e. Based on per capita income averages and distribution data estimated parametrically from grouped household survey data. f. Estimated nonparametrically from nominal income per capita distributions based on unit-record household survey data. g. PPP conversion factor based on urban prices. h. Population-weighted average of urban and rural estimates. i. Based on benchmark national PPP estimate rescaled to account for cost-of-living differences in urban and rural areas. j. Estimated nonparametrically from nominal consumption per capita distributions based on unit-record household survey data.

30 

World Development Indicators 2013

Front

?

User guide

World view People Environment


Poverty rates Trends in poverty indicators by region, 1990–2015 Region

1990

1993

1996

1999

2002

2005

2008

2010 provisional 2015 projection

Trend, 1990–2010

Share of population living on less than 2005 PPP $1.25 a day (%) 56.2

50.7

35.9

35.6

27.6

17.1

14.3

12.5

5.5

1.9

2.9

3.9

3.8

2.3

1.3

0.5

0.7

0.4

Latin America & Caribbean

12.2

11.4

11.1

11.9

11.9

8.7

6.5

5.5

4.9

Middle East & North Africa

5.8

4.8

4.8

5.0

4.2

3.5

2.7

2.4

2.6

East Asia & Pacific Europe & Central Asia

South Asia

53.8

51.7

48.6

45.1

44.3

39.4

36.0

31.0

23.2

Sub-­Saharan Africa

56.5

59.4

58.1

57.9

55.7

52.3

49.2

48.5

42.3

Total

43.1

41.0

34.8

34.1

30.8

25.1

22.7

20.6

15.5

People living on less than 2005 PPP $1.25 a day (millions) 926

871

640

656

523

332

284

251

115

9

14

18

18

11

6

2

3

2

Latin America & Caribbean

53

53

54

60

63

48

37

32

30

Middle East & North Africa

13

12

12

14

12

10

9

8

9

South Asia

617

632

631

619

640

598

571

507

406

Sub-­Saharan Africa

290

330

349

376

390

395

399

414

408

1,908

1,910

1,704

1,743

1,639

1,389

1,302

1,215

970

East Asia & Pacific Europe & Central Asia

Total

Regional distribution of people living on less than $1.25 a day (% of total population living on less than $1.25 a day) 48.5

45.6

37.6

37.6

31.9

23.9

21.8

20.7

11.8

Europe & Central Asia

0.5

0.7

1.1

1.0

0.6

0.5

0.2

0.3

0.2

Latin America & Caribbean

2.8

2.7

3.1

3.4

3.8

3.4

2.9

2.7

3.1

Middle East & North Africa

0.7

0.6

0.7

0.8

0.7

0.8

0.7

0.7

1.0

South Asia

32.3

33.1

37.0

35.5

39.1

43.1

43.8

41.7

41.9

Sub-­Saharan Africa

15.2

17.3

20.5

21.6

23.8

28.4

30.7

34.1

42.1

East Asia & Pacific

Average daily consumption or income of people living on less than 2005 PPP $1.25 a day (2005 PPP $) East Asia & Pacific

0.83

0.85

0.89

0.87

0.89

0.95

0.95

0.97

..

Europe & Central Asia

0.90

0.90

0.91

0.92

0.93

0.88

0.88

0.85

..

Latin America & Caribbean

0.71

0.69

0.68

0.67

0.65

0.63

0.62

0.60

..

Middle East & North Africa

1.02

1.02

1.01

1.01

1.01

0.99

0.97

0.96

..

South Asia

0.88

0.89

0.91

0.91

0.92

0.94

0.95

0.96

..

Sub-­Saharan Africa

0.69

0.68

0.69

0.69

0.70

0.71

0.71

0.71

..

Total

0.82

0.83

0.85

0.84

0.85

0.87

0.87

0.87

..

Survey coverage (% of total population represented by underlying survey data) East Asia & Pacific

92.4

93.3

93.7

93.4

93.5

93.2

93.6

93.5

..

Europe & Central Asia

81.5

87.3

97.1

93.9

96.3

94.7

89.9

85.3

..

Latin America & Caribbean

94.9

91.8

95.9

97.7

97.5

95.9

94.5

86.9

..

Middle East & North Africa

76.8

65.3

81.7

70.0

21.5

85.7

46.7

30.8

..

South Asia

96.5

98.2

98.1

20.1

98.0

98.0

97.9

94.5

..

Sub-­Saharan Africa

46.0

68.8

68.0

53.1

65.7

82.7

81.7

64.1

..

Total

86.4

89.4

91.6

68.2

87.8

93.0

90.2

84.7

..

Source: World Bank PovcalNet.

Economy

States and markets

Global links

Back

World Development Indicators 2013 31


Poverty rates About the data The World Bank produced its first global poverty estimates for

The low frequency and lack of comparability of the data available

developing countries for World Development Report 1990: Poverty

in some countries create uncertainty over the magnitude of poverty

(World Bank 1990) using household survey data for 22 coun-

reduction. The table on trends in poverty indicators reports the

tries (Ravallion, Datt, and van de Walle 1991). Since then there

percentage of the regional and global population represented by

has been considerable expansion in the number of countries

household survey samples collected during the reference year or

that field household income and expenditure surveys. The World

during the two preceding or two subsequent years (in other words,

Bank’s Development Research Group maintains a database that

within a five-year window centered on the reference year). Data cov-

is updated regularly as new survey data become available (and

erage in Sub-­Saharan Africa and the Middle East and North Africa

thus may contain more recent data or revisions that are not incor-

remains low and variable. The need to improve household survey

porated into the table) and conducts a major reassessment of

programs for monitoring poverty is clearly urgent. But institutional,

progress against poverty about every three years.

political, and financial obstacles continue to limit data collection,

This year the database has been updated with global and regional

analysis, and public access.

extreme poverty estimates for 2010, which are provisional due to low coverage in household survey data availability for recent years

Data quality

(2008–12). The projections to 2015 of poverty rates use the 2010

Besides the frequency and timeliness of survey data, other data

provisional estimates as a baseline and assume that average house-

quality issues arise in measuring household living standards. The

hold income or consumption will grow in line with the aggregate eco-

surveys ask detailed questions on sources of income and how it

nomic projections reported in this year’s Global Monitoring Report

was spent, which must be carefully recorded by trained personnel.

(World Bank 2013) but that inequality within countries will remain

Income is generally more difficult to measure accurately, and con-

unchanged. This methodology was first used and described in the

sumption comes closer to the notion of living standards. And income

Global Economic Prospects report (World Bank 2000). Estimates of

can vary over time even if living standards do not. But consumption

the number of people living in extreme poverty are based on popula-

data are not always available: the latest estimates reported here

tion projections in the World Bank’s HealthStats database (http://

use consumption for about two-thirds of countries.

datatopics.worldbank.org/hnp).

However, even similar surveys may not be strictly comparable

PovcalNet (http://iresearch.worldbank.org/PovcalNet) is an

because of differences in timing, sampling frames, or the quality

interactive computational tool that allows users to replicate these

and training of enumerators. Comparisons of countries at different

internationally comparable $1.25 and $2 a day global, regional and

levels of development also pose a potential problem because of dif-

country-level poverty estimates and to compute poverty measures

ferences in the relative importance of the consumption of nonmarket

for custom country groupings and for different poverty lines. The

goods. The local market value of all consumption in kind (includ-

Poverty and Equity Data portal (http://povertydata.worldbank.org/

ing own production, particularly important in underdeveloped rural

poverty/home) provides access to the database and user-friendly

economies) should be included in total consumption expenditure, but

dashboards with graphs and interactive maps that visualize trends in

may not be. Most survey data now include valuations for consump-

key poverty and inequality indicators for different regions and coun-

tion or income from own production, but valuation methods vary.

tries. The country dashboards display trends in poverty measures

The statistics reported here are based on consumption data or,

based on the national poverty lines (see online table 2.7) alongside

when unavailable, on income data. Analysis of some 20 countries

the internationally comparable estimates in the table, produced

for which both were available from the same surveys found income

from and consistent with PovcalNet.

to yield a higher mean than consumption but also higher inequality. When poverty measures based on consumption and income were

Data availability

compared, the two effects roughly cancelled each other out: there

The World Bank’s internationally comparable poverty monitoring

was no significant statistical difference.

database now draws on income or detailed consumption data

Invariably some sampled households do not participate in

collected from interviews with 1.23 million randomly sampled

surveys because they refuse to do so or because nobody is

households through more than 850 household surveys collected

at home during the interview visit. This is referred to as “unit

by national statistical offices in nearly 130 countries. Despite prog-

nonresponse” and is distinct from “item nonresponse,” which

ress in the last decade, the challenges of measuring poverty remain.

occurs when some of the sampled respondents participate but

The timeliness, frequency, quality, and comparability of household

refuse to answer certain questions, such as those pertaining to

surveys need to increase substantially, particularly in the poorest

income or consumption. To the extent that survey nonresponse

countries. The availability and quality of poverty monitoring data

is random, there is no concern regarding biases in survey-based

remain low in small states, fragile situations, and low-income coun-

inferences; the sample will still be representative of the popula-

tries and even some middle-income countries.

tion. However, households with different income might not be equally likely to respond. Richer households may be less likely

32 

World Development Indicators 2013

Front

?

User guide

World view People Environment


Poverty rates to participate because of the high opportunity cost of their time

Definitions

or concerns about intrusion in their affairs. It is conceivable that

• International poverty line in local currency is the international

the poorest can likewise be underrepresented; some are home-

poverty lines of $1.25 and $2.00 a day in 2005 prices, converted

less or nomadic and hard to reach in standard household survey

to local currency using the PPP conversion factors estimated by

designs, and some may be physically or socially isolated and

the International Comparison Program. • Survey year is the year in

thus less likely to be interviewed. This can bias both poverty and

which the underlying data were collected or, when the data collection

inequality measurement if not corrected for (Korinek, Mistiaen,

period bridged two calendar years, the year in which most of the data

and Ravallion 2007).

were collected. • Population below $1.25 a day and population below $2 a day are the percentages of the population living on less

International poverty lines

than $1.25 a day and $2 a day at 2005 international prices. As a

International comparisons of poverty estimates entail both concep-

result of revisions in PPP exchange rates, consumer price indexes,

tual and practical problems. Countries have different definitions of

or welfare aggregates, poverty rates for individual countries cannot

poverty, and consistent comparisons across countries can be diffi-

be compared with poverty rates reported in earlier editions. The

cult. Local poverty lines tend to have higher purchasing power in rich

PovcalNet online database and tool always contain the most recent

countries, where more generous standards are used, than in poor

full time series of comparable country data. • Poverty gap is the

countries. Poverty measures based on an international poverty line

mean shortfall from the poverty line (counting the nonpoor as hav-

attempt to hold the real value of the poverty line constant across

ing zero shortfall), expressed as a percentage of the poverty line.

countries, as is done when making comparisons over time. Since

This measure reflects the depth of poverty as well as its incidence.

World Development Report 1990 the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what

Data sources

poverty means in the world’s poorest countries. The welfare of people

The poverty measures are prepared by the World Bank’s Develop-

living in different countries can be measured on a common scale by

ment Research Group. The international poverty lines are based on

adjusting for differences in the purchasing power of currencies. The

nationally representative primary household surveys conducted by

commonly used $1 a day standard, measured in 1985 international

national statistical offices or by private agencies under the supervi-

prices and adjusted to local currency using purchasing power parities

sion of government or international agencies and obtained from

(PPPs), was chosen for World Development Report 1990 because it

government statistical offices and World Bank Group country depart-

was typical of the poverty lines in low-income countries at the time.

ments. For details on data sources and methods used in deriving

Early editions of World Development Indicators used PPPs from the

the World Bank’s latest estimates, see http://iresearch.worldbank

Penn World Tables to convert values in local currency to equivalent

.org/PovcalNet/index.htm.

purchasing power measured in U.S dollars. Later editions used 1993 consumption PPP estimates produced by the World Bank.

References

International poverty lines were recently revised using the new

Chen, Shaohua, and Martin Ravallion. 2011. “The Developing World Is

data on PPPs compiled in the 2005 round of the International Com-

Poorer Than We Thought, But No Less Successful in the Fight Against

parison Program, along with data from an expanded set of house-

Poverty.” Quarterly Journal of Economics 125(4): 1577–1625.

hold income and expenditure surveys. The new extreme poverty

Korinek, Anton, Johan A. Mistiaen, and Martin Ravallion. 2007. “An

line is set at $1.25 a day in 2005 PPP terms, which represents the

Econometric Method of Correcting for Unit Nonresponse Bias in

mean of the poverty lines found in the poorest 15 countries ranked

Surveys.” Journal of Econometrics 136: 213–35.

by per capita consumption. The new poverty line maintains the same

Ravallion, Martin, Guarav Datt, and Dominique van de Walle. 1991.

standard for extreme poverty—the poverty line typical of the poorest

“Quantifying Absolute Poverty in the Developing World.” Review of

countries in the world—but updates it using the latest information on the cost of living in developing countries. PPP exchange rates are

Income and Wealth 37(4): 345–61. Ravallion, Martin, Shaohua Chen, and Prem Sangraula. 2009. “Dol-

used to estimate global poverty because they take into account the

lar a Day Revisited.” World Bank Economic Review 23(2): 163–84.

local prices of goods and services not traded internationally. But

World Bank. 1990. World Development Report 1990: Poverty. Wash-

PPP rates were designed for comparing aggregates from national accounts, not for making international poverty comparisons. As a result, there is no certainty that an international poverty line measures the same degree of need or deprivation across countries. So-called poverty PPPs, designed to compare the consumption of the poorest people in the world, might provide a better basis for comparison of poverty across countries. Work on these measures

ington, DC. ———. 2000. Global Economic Prospects and the Developing Countries. Washington, DC. ———. 2008. Poverty Data: A Supplement to World Development Indicators 2008. Washington, DC. ———. 2013. Global Monitoring Report: Rural-Urban Dynamics and the Millennium Development Goals. Washington, DC.

is ongoing.

Economy

States and markets

Global links

Back

World Development Indicators 2013 33


PEOPLE

34â&#x20AC;&#x192;

World Development Indicators 2013

Front

?

User guide

World view

People Environment


The indicators in the People section present demographic trends and forecasts alongside indicators of education, health, jobs, social protection, poverty, and the distribution of income. Together they provide a multidimensional portrait of human development. Data updates in this edition include provisional estimates of global and regional extreme poverty rates for 2010—measured as the proportion of the population living on less than $1.25 a day. The availability, frequency, and quality of poverty monitoring data remain low, especially in small states and in countries and territories with fragile situations. While estimates may change marginally as additional country data become available, it is now clear that the first Millennium Development Goal target—cutting the global extreme poverty rate to half its 1990 level—was achieved before the 2015 target date. In 1990, the benchmark year for the Millennium Development Goals, the extreme poverty rate was 43.1 percent. Estimates for 2010 show that the extreme poverty rate had fallen to 20.6 percent. In addition to extreme poverty rates, the People section includes many other indicators used to monitor the Millennium Development Goals. Following the adoption of the Millennium Declaration by the United Nations General Assembly in 2000, various international agencies including the World Bank resolved to invest in using highquality harmonized data to monitor the Millennium Development Goals. These efforts range from providing technical and financial assistance to strengthen country statistical systems to fostering international collaboration through participation in the United Nations Inter-Agency and Expert Group on the Millennium Development Goal Indicators and several thematic

Economy

States and markets

inter-agency groups. These forums bring together agency subject matter specialists with leading academic and local experts. Successful thematic inter-agency efforts have improved estimates on child mortality, child malnutrition, as well as maternal mortality, one of the most challenging indicators to measure. For 2013 the People section includes improved child malnutrition indicators produced by the United Nations Children’s Fund, the World Health Organization, and the World Bank using a harmonized dataset and the same statistical methodology to estimate global, regional, and income group aggregates. Another result is the improvement in monitoring HIV prevalence. Initial efforts relied solely on country surveillance systems that collected data from pregnant women who attended sentinel antenatal clinics. Now the methodology measuring this indicator uses all available ­information— including blood test data collected through nationally representative sample s ­ urveys—and the models account for the effects of anti­retro­ viral therapy and urbanization (see About the data for online table 2.20). In addition to providing insights into differences between countries and between groups of countries, the People section includes indicators disaggregated by location and by socioeconomic and demographic strata within countries, such as gender, age, and wealth quintile. These data provide a deeper perspective on the disparities within countries. New indicators for 2013 include sex-disaggregated data on the under-five mortality rate, sex-disaggregated youth labor force participation rates, and numerous indicators from the World Bank’s Atlas of Social Protection Indicators of Resilience and Equity database.

Global links

Back

2

World Development Indicators 2013 35


Highlights East Asia & Pacific: Narrowing gaps in access to improved sanitation facilities and water sources During the past 20 years the share of the developing world’s population

Share of population with access (%) To improved sanitation facilities 100

To improved water sources 90

86

75

with access to improved sanitation facilities and water sources has risen substantially. East Asia and Pacific has made above-average

90

progress on improving both and narrowing the gap between them,

71

68

driven by a rapid expansion in access to improved sanitation from

71

66

30 percent in 1990 to 66 percent in 2010. In South Asia progress on

61

56

50

access to an improved water source was almost on par with East Asia

48

and Pacific, but access to improved sanitation facilities remains very

38

37 30

25

26

22

low. Indeed, the region fares only marginally better than Sub-­Saharan

31

Africa, which progressed substantially slower over the past two decades. But both regions made progress on expanding the share of

0

1990 2010 Developing countries

1990 2010 East Asia & Pacific

1990 2010 South Asia

the population with access to an improved water source.

1990 2010 Sub-Saharan Africa

Source: Online table 2.16.

Europe & Central Asia: Variation in prevalence of underweight children Malnourishment in children has been linked to poverty, low levels of

Prevalence of child malnutrition, underweight, most recent year, 2005–11 (% of children under age 5)

education, and poor access to health services. It increases the risk of

25

death, inhibits cognitive development, and can adversely affect health status during adulthood. Adequate nutrition is a cornerstone for devel-

20

opment, health, and the survival of current and future generations. 15

Europe and Central Asia has the lowest prevalence (1.5 percent) of underweight children among developing regions, but there is substan-

10

tial variation across countries. At 3.2 percent, prevalence in Moldova is more like that in Latin America and the Caribbean countries; at

5

5.3 percent, prevalence in Armenia is more like that in East Asia and Sub-Saharan Africa

Middle East & North Africa

East Asia & Pacific

Latin America & Caribbean

Europe & Central Asia

Tajikistan

Albania

Armenia

Moldova

Bulgaria

Pacific countries; and at 6.3 percent, prevalence in Albania is more Georgia

0

like that in Middle East and North African countries. Tajikistan, a lowincome country, at 15 percent has the highest proportion of underweight children in the region.

Source: Online table 2.18.

Latin America & Caribbean: Income inequality falling but remains among the world’s highest T he Gini coefficient, a common indicator of income inequality, mea-

Gini coefficient, most recent value, 2000–11 65

sures how much the per capita income distribution within a country Latin America & Caribbean countries Other upper middle income countries Other countries

55

deviates from perfect equality. (A Gini coefficient of 0 represents

Inequality increased

perfect equality, and a value of 100 perfect inequality.) Trends in developing countries over the past two decades suggest that many

Inequality unchanged

countries have become less unequal, but trends differ by region and by income. Inequality in Latin America and the Caribbean fell notably

45

in almost all upper middle-income countries but remains among the

Inequality decreased

highest w ­ orldwide. The Gini coefficient is higher than the Latin America and the Caribbean average in only two other upper middle-

35

income countries and in only a few low- and lower middle-­income 25 25

countries. 35

45

55

65

Gini coefficient (most recent value, 1990–99) Source: Online table 2.9 and World Bank PovcalNet.

36 

World Development Indicators 2013

Front

?

User guide

World view

People Environment


Middle East & North Africa: Many educated women are not participating in the labor force More than 70 percent of girls in the Middle East and North Africa

Gross secondary enrollment ratio for girls (% of relevant age group) Labor force participation rate for women (% of women ages 15 and older)

attend secondary school (higher than most developing countries), but labor force participation rates have stagnated at around 20 percent

100

since 1990 (lower than most developing countries). Eight of the ten countries with the largest gap between their labor force participation

75

rate and secondary enrollment ratio are in the Middle East and North Africa. (Costa Rica and Sri Lanka are the only countries in the top 10

50

not from the region.) Morocco and the Republic of Yemen have the smallest gap, but they also have the lowest secondary enrollment ratio.

25

Middle East & North Africa, 2011 Developing countries, 2011

Yemen, Rep., 2011

Morocco, 2007

Egypt, Arab Rep., 2010

Iran, Islamic Rep., 2011

online table 2.4).

Lebanon, 2011

has the largest gender gap in the share of vulnerable employment (see

Jordan, 2010

0

Algeria, 2009

and in what condition women work are also important. The region also

Tunisia, 2009

In addition to whether women participate in economic activities, where

Source: Online tables 2.2 and 2.11.

South Asia: In India more girls than boys die before their fifth birthday The ratio of girls’ to boys’ under-five mortality rate varies across developing countries, but on average it is 0.96. East Asia and Pacific

Ratio of girls’ to boys’ under-five mortality rate, 2011 Lowest in region

has the largest variation among developing regions. At one extreme

East Asia Palau 0.59 & Pacific

is Palau, where mortality rates for boys are two-thirds higher than that for girls. Biologically, boys are more vulnerable than girls, so under-five mortality rates are usually higher for boys than girls. This biological advantage can be reversed, however, by socioeconomic factors such as gender inequalities in nutrition and medical care or discrimination against girls. India and the Solomon Islands are the

Europe & Central Asia

0.92 Azerbaijan

Jamaica 0.75

Middle East & North Africa

0.93 Grenada

Tunisia 0.85

South Asia

fifth birthday. In India under-five mortality rates for girls and boys have at around 1.1 since 1990.

1.06 Solomon Islands

Belarus 0.73

Latin America & Caribbean

only developing countries where more girls than boys die before their improved, but the ratio of girls’ to boys’ under-five deaths has stayed

Highest in region

0.96 Iran, Islamic Rep.

Sri Lanka 0.81

Sub-Saharan Africa

1.09 India

Eritrea 0.83

0.50

0.98 South Sudan

0.75

1.00 (parity)

1.25

Source: Online table 2.21.

Sub-­Saharan Africa: Different demographic transition paths at varying speeds Today, one of every nine children in Sub-­S aharan Africa dies before their fifth birthday, and fertility rates there remain higher than any-

Under-five mortality rate (per 1,000 live births) 400

Côte d’Ivoire Gabon Mali Niger Sub-Saharan Africa

where else in the developing world. Sub-­S aharan countries progressed over the past four decades, but they are moving along different paths at varying speeds. Gabon, ahead of the curve, had the

1970 1970 1990

300

under-five mortality and total fertility rates in 1980 that the region has today. Niger made little progress between 1970 and 1990 but

1970

200

has since seen rapid improvements in its under-five mortality rate

1980

and a marginal decline in its fertility rate. In 1970 Côte d’Ivoire had an average mortality rate but a high fertility rate. Its mortality rate

2010

100

declined quickly until 1980, thereafter its fertility rate declined rapidly and overtook the region by 2010. Mali, which had the highest under-five mortality rate in 1970, took until 2010 to reach the rate

1970

2010

2010

1980

2010

2010

0 3

4

5

6

7

8

9

Total fertility rate (births per woman)

the region passed in 1990.

Source: Online table 2.21.

Economy

States and markets

Global links

Back

World Development Indicators 2013 37


2 People Prevalence Under-five of child mortality malnutrition, rate underweight

estimate 1,000 % of per 100,000 women ages population % of relevant live births 15–19 ages 15–49 age group

% of children under age 5

per 1,000 live births

2005–11 a

2011

2010

2011

2011

2011

Afghanistan

% ages 15–24

% ages 15 and older

workers % of total employment

% of total labor force

% of total

2005–11a

2011

2007–11 a

2007–11 a

2007–11 a

..

101

460

103

<0.1

..

..

49

..

..

..

Albania

6.3

14

27

16

..

..

99

60

..

13.8

..

Algeria

3.7

30

97

6

..

94

92

44

..

10.0

..

American Samoa

..

..

..

..

..

..

..

..

..

..

..

Andorra

..

3

..

..

..

63

..

..

..

..

..

15.6

158

450

153

2.1

..

73

70

..

..

..

..

8

..

..

..

98

..

..

..

..

..

Argentina

2.3

14

77

55

0.4

..

99

61

19

7.2

..

Armenia

5.3

18

30

34

0.2

83

100

59

38

28.6

22 40

Angola Antigua and Barbuda

Aruba

..

..

..

28

..

..

99

..

4

5.7

Australia

..

5

7

13

0.2

..

..

66

9

5.1

37

Austria

..

4

4

10

0.4

..

..

61

9

4.1

27

8.4

45

43

32

<0.1

93

100

65

55

5.4

7

..

16

47

29

2.8

..

..

74

..

13.7

52 ..

Azerbaijan Bahamas, The Bahrain

..

10

20

15

..

..

100

71

2

..

41.3

46

240

70

<0.1

..

77

71

..

5.0

..

..

20

51

41

0.9

111

..

70

..

11.2

47

Belarus

1.3

6

4

21

0.4

104

100

56

..

..

..

Belgium

..

4

8

12

0.3

..

..

54

10

7.1

30

Bangladesh Barbados

Belize

4.9

17

53

72

2.3

110

..

65

..

8.2

..

Benin

20.2

106

350

100

1.2

75

55

73

..

..

..

..

..

..

..

..

..

..

..

..

..

..

Bhutan

12.7

54

180

46

0.3

74

72

71

3.1

27

Bolivia

4.5

51

190

75

0.3

..

99

72

55

3.4

29

Bosnia and Herzegovina

1.6

8

8

14

..

76

100

46

25

27.6

..

11.2

26

160

45

23.4

..

95

77

..

..

..

2.2

16

56

76

0.3

..

98

70

25

8.3

36

Bermuda

Botswana Brazil

103b

Brunei Darussalam

..

7

24

23

..

120

100

66

..

..

..

Bulgaria

..

12

11

38

<0.1

..

98

54

9

11.2

37 ..

Burkina Faso

26.0

146

300

119

1.1

..

39

84

..

3.3

Burundi

35.2

139

800

20

1.3

62

78

83

..

..

..

Cambodia

29.0

43

250

35

0.6

90

87

83

69

0.2

21

Cameroon

16.6

127

690

118

4.6

78

83

71

76

3.8

..

Canada

..

6

12

12

0.3

..

..

67

..

7.4

36

Cape Verde

..

21

79

72

1.0

95

98

67

..

..

..

Cayman Islands

..

..

..

..

..

..

99

..

..

4.0

44

Central African Republic

28.0

164

890

100

4.6

43

65

79

..

..

..

Chad

..

169

1,100

143

3.1

38

47

72

..

..

..

Channel Islands

..

..

..

9

..

..

..

..

..

..

..

Chile

0.5

9

25

56

0.5

..

99

60

24

7.1

..

China

3.4

15

37

9

<0.1

..

99

74

..

4.1

..

..

..

..

4

..

91

..

59

7

3.4

32

Hong Kong SAR, China Macao SAR, China

38 

Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female mortality fertility of HIV completion literacy participation employment legislators, ratio rate rate rate rate senior Unpaid family officials, and workers and managers Modeled births per own-account

..

..

..

4

..

..

100

72

4

2.6

31

Colombia

3.4

18

92

69

0.5

112

98

67

49

11.6

..

Comoros

..

79

280

52

<0.1

..

86

58

..

..

..

Congo, Dem. Rep.

28.2

168

540

177

..

..

65

71

..

..

..

Congo, Rep.

11.8

99

560

114

3.3

..

80

71

..

..

..

Front

?

World Development Indicators 2013

User guide

World view

People Environment


People 2 Prevalence Under-five of child mortality malnutrition, rate underweight

Costa Rica Côte d’Ivoire Croatia Cuba

% of children under age 5

per 1,000 live births

2005–11 a

2011

Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female mortality fertility of HIV completion literacy participation employment legislators, ratio rate rate rate rate senior Unpaid family officials, and workers and managers Modeled births per own-account

estimate 1,000 % of per 100,000 women ages population % of relevant live births 15–19 ages 15–49 age group 2010

2011

2011

2011

% ages 15–24

% ages 15 and older

workers % of total employment

% of total labor force

% of total

2005–11a

2011

2007–11 a

2007–11 a

2007–11 a

1.1

10

40

63

0.3

99

98

63

20

7.7

29.4

115

400

110

3.0

59

67

67

..

..

35 ..

..

5

17

13

<0.1

..

100

53

18

13.4

25 ..

1.3

6

73

44

0.2

99

100

57

..

2.5

Curaçao

..

..

..

..

..

..

..

..

..

..

..

Cyprus

..

3

10

6

..

..

100

65

14

7.7

14

Czech Republic

..

4

5

10

<0.1

..

..

59

14

6.7

26

Denmark

..

4

12

5

0.2

..

..

64

6

7.6

28

29.6

90

200

20

1.4

57b

..

52

..

..

..

..

12

..

..

..

94

..

..

..

..

..

3.4

25

150

105

0.7

92

97

65

37

12.4

31

Djibouti Dominica Dominican Republic Ecuador

..

23

110

81

0.4

112

99

68

42

4.2

..

Egypt, Arab Rep.

6.8

21

66

42

<0.1

..

88

49

27

9.0

11

El Salvador

6.6

15

81

77

0.6

101

96

62

38

7.0

29

Equatorial Guinea

..

118

240

116

4.7

52

98

87

..

..

..

Eritrea

..

68

240

56

0.6

..

89

85

..

..

..

Estonia

..

4

2

18

1.3

..

100

62

5

12.5

36

Ethiopia

29.2

77

350

53

1.4

58

55

84

..

..

..

Faeroe Islands

..

..

..

..

..

..

..

..

..

..

..

Fiji

..

16

26

43

<0.1

103

..

60

..

8.6

..

Finland

..

3

5

9

<0.1

..

..

60

9

7.7

32

France

..

4

8

6

0.4

..

..

56

7

9.3

39

French Polynesia

..

..

..

49

..

..

..

58

..

11.7

..

Gabon

..

66

230

83

5.0

..

98

61

..

..

..

15.8

101

360

69

1.5

66

67

78

..

..

..

1.1

21

67

41

0.2

..

100

64

63

15.1

34 30

Gambia, The Georgia Germany

1.1

4

7

7

0.2

..

..

60

7

5.9

Ghana

14.3

78

350

64

1.5

99 b

81

69

..

..

..

Greece

1.1

4

3

10

0.2

..

99

55

29

17.7

23

Greenland

..

..

..

..

..

..

..

..

..

..

..

Grenada

..

13

24

37

..

..

..

..

..

..

..

Guam

..

..

..

50

..

..

..

61

..

..

..

Guatemala

13.0

30

120

103

0.8

..

87

68

..

4.1

..

Guinea

20.8

126

610

138

1.4

..

63

72

..

..

..

Guinea-Bissau

17.2

161

790

99

2.5

..

72

73

..

..

..

Guyana

11.1

36

280

57

1.1

85

..

60

..

21.0

..

Haiti

18.9

70

350

42

1.8

..

72

65

..

..

..

8.6

21

100

87

..

101

95

62

53

4.8

..

..

6

21

14

<0.1

..

99

51

7

10.9

40 40

Honduras Hungary Iceland

..

3

5

12

0.3

..

..

75

8

7.1

India

43.5

61

200

77

..

..

81

56

81

3.5

14

Indonesia

18.6

32

220

43

0.3

..

99

68

57

6.6

22 13

Iran, Islamic Rep.

..

25

21

26

0.2

106

99

45

42

10.5

7.1

38

63

88

..

..

83

42

..

..

..

Ireland

..

4

6

11

0.3

..

..

61

12

14.4

33

Isle of Man

..

..

..

..

..

..

..

..

..

..

..

Israel

..

4

7

14

0.2

..

..

57

7

5.6

32

Iraq

Economy

States and markets

Global links

Back

World Development Indicators 2013 39


2 People Prevalence Under-five of child mortality malnutrition, rate underweight % of children under age 5

per 1,000 live births

2005–11 a

2011

Italy

estimate 1,000 % of per 100,000 women ages population % of relevant live births 15–19 ages 15–49 age group 2010

2011

2011

2011

% ages 15–24

% ages 15 and older

workers % of total employment

% of total labor force

% of total

2005–11a

2011

2007–11 a

2007–11 a

2007–11 a

..

4

4

5

0.4

..

100

48

18

8.4

25

1.9

18

110

71

1.8

..

95

64

37

12.7

..

..

3

5

6

<0.1

..

..

60

11

4.5

..

Jordan

1.9

21

63

24

..

..

99

42

9

12.9

..

Kazakhstan

4.9

28

51

26

0.2

100

72

30

5.4

38

16.4

73

360

99

6.2

..

93

67

..

..

..

..

47

..

..

..

..

..

..

..

..

..

18.8

33

81

1

..

..

100

78

..

..

..

..

5

16

5

<0.1

..

..

60

25

3.4

10

Jamaica Japan

Kenya Kiribati Korea, Dem. Rep. Korea, Rep.

108b

Kosovo

..

..

..

..

..

..

..

..

..

45.4

..

Kuwait

1.7

11

14

14

..

..

99

68

..

..

..

Kyrgyz Republic

2.7

31

71

33

0.4

96

100

67

..

8.2

..

31.6

42

470

32

0.3

93

84

78

..

..

..

..

8

34

14

0.7

93

100

61

8

15.4

45

Lao PDR Latvia Lebanon

5.2

9

25

16

<0.1

87

99

46

28

9.0

8

Lesotho

13.5

86

620

63

23.3

68

92

66

..

25.3

..

Liberia

20.4

78

770

127

1.0

66

77

61

79

3.7

..

5.6

16

58

3

..

..

100

53

..

..

..

Liechtenstein

..

2

..

..

..

101

..

..

..

..

..

Lithuania

..

6

8

17

<0.1

95

100

59

8

15.4

38

..

3

20

9

0.3

..

..

57

6

4.9

24

1.8

10

10

19

..

..

99

56

23

31.4

28 ..

Libya

Luxembourg Macedonia, FYR Madagascar

..

62

240

125

0.3

73

65

86

..

..

Malawi

13.8

83

460

108

10.0

71

87

83

..

..

..

Malaysia

12.9

7

29

11

0.4

..

98

60

22

3.4

25 ..

Maldives

17.8

11

60

11

<0.1

107

99

66

..

..

Mali

27.9

176

540

172

1.1

55

44

53

83

..

..

..

6

8

13

<0.1

..

98

51

9

6.4

23 ..

Malta Marshall Islands Mauritania Mauritius Mexico Micronesia, Fed. Sts. Moldova Monaco

..

26

..

..

..

97

..

..

..

..

15.9

112

510

73

1.1

..

68

54

..

31.2

..

..

15

60

33

1.0

..

97

60

15

7.9

23 31

3.4

16

50

67

0.3

104

98

62

29

5.3

..

42

100

20

..

..

..

..

..

..

..

3.2

16

41

30

0.5

91

99

42

29

6.7

38

..

4

..

..

..

..

..

..

..

..

..

Mongolia

5.3

31

63

19

<0.1

115

96

60

58

..

47

Montenegro

2.2

7

8

15

..

99 b

99

..

..

19.7

31

Morocco

3.1

33

100

12

0.2

99 b

79

50

52

8.9

13

Mozambique

18.3

103

490

129

11.3

56

72

85

..

..

..

Myanmar

22.6

62

200

13

0.6

..

96

79

..

..

..

Namibia

17.5

42

200

58

13.4

..

93

64

14

37.6

..

Nepal

29.1

48

170

90

0.3

..

83

84

..

2.7

..

Netherlands

..

4

6

4

0.2

..

..

65

11

4.4

30

New Caledonia

..

..

..

20

..

..

100

58

..

..

..

New Zealand

..

6

15

21

<0.1

..

..

68

12

6.5

40

Nicaragua Niger

40 

Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female mortality fertility of HIV completion literacy participation employment legislators, ratio rate rate rate rate senior Unpaid family officials, and workers and managers Modeled births per own-account

World Development Indicators 2013

5.7

26

95

106

0.2

..

87

63

47

8.0

..

39.9

125

590

196

0.8

46

37

65

..

..

..

Front

?

User guide

World view People view People Environment Environment


People 2 Prevalence Under-five of child mortality malnutrition, rate underweight

Nigeria

Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female mortality fertility of HIV completion literacy participation employment legislators, ratio rate rate rate rate senior Unpaid family officials, and workers and managers Modeled births per own-account

estimate 1,000 % of per 100,000 women ages population % of relevant live births 15–19 ages 15–49 age group

% of children under age 5

per 1,000 live births

2005–11 a

2011

2010

2011

2011

2011

% ages 15–24

% ages 15 and older

workers % of total employment

% of total labor force

% of total

2005–11a

2011

2007–11 a

2007–11 a

2007–11 a

26.7

124

630

113

3.7

..

72

56

..

..

Northern Mariana Islands

..

..

..

..

..

..

..

..

..

..

..

Norway

..

3

7

8

0.2

..

..

66

5

3.3

31

Oman Pakistan Palau Panama Papua New Guinea Paraguay Peru

..

8.6

9

32

9

..

107

98

61

..

..

..

30.9

72

260

29

<0.1

67

71

53

63

5.0

3

..

19

..

..

..

..

..

..

..

..

..

3.9

20

92

77

0.8

101

98

66

29

4.5

46

18.1

58

230

63

0.7

..

68

72

..

4.0

..

3.4

22

99

68

0.3

..

99

72

42

5.6

34

4.5

18

67

50

0.4

97

97

76

40

7.8

19

20.7

25

99

48

<0.1

..

98

64

41

7.0

55

Poland

..

6

5

13

<0.1

..

100

56

18

9.6

38

Portugal

..

3

8

13

0.7

..

100

62

16

12.7

33

Puerto Rico

..

..

20

51

..

..

87

45

..

15.7

43

Qatar

..

8

7

16

..

96

97

86

0

0.6

10

Romania

..

13

27

29

<0.1

..

97

56

32

7.4

31

Russian Federation

..

12

34

25

..

..

100

63

6

6.6

37

11.7

54

340

36

2.9

..

77

86

..

2.4

..

Samoa

..

19

100

26

..

98

99

61

..

..

..

San Marino

..

2

..

..

..

93

..

..

..

2.6

18

14.4

89

70

58

1.0

115

95

60

..

..

..

5.3

9

24

20

..

106

98

50

..

5.4

8

19.2

65

370

93

0.7

63

65

77

..

..

..

1.8

7

12

20

<0.1

99

99

..

27

19.2

33 ..

Philippines

Rwanda

São Tomé and Príncipe Saudi Arabia Senegal Serbia Seychelles

..

14

..

..

..

125

99

..

..

..

21.3

185

890

112

1.6

74

59

68

..

..

..

Singapore

..

3

3

6

<0.1

..

100

67

10

2.9

34

Sint Maarten

..

..

..

..

..

..

..

..

..

..

..

Slovak Republic

..

8

6

17

<0.1

..

..

59

12

13.5

31

Sierra Leone

Slovenia

..

3

12

5

<0.1

..

100

59

13

8.2

38

Solomon Islands

11.5

22

93

66

..

..

..

67

..

..

..

Somalia

32.8

180

1,000

68

0.7

..

..

57

..

..

..

8.7

47

300

52

17.3

..

98

52

10

24.7

31

South Sudan

..

121

..

..

3.1

..

..

..

..

..

..

Spain

..

4

6

11

0.4

..

100

59

11

21.6

30

South Africa

Sri Lanka

21.6

12

35

22

<0.1

..

98

55

42

4.9

24

St. Kitts and Nevis

..

7

..

..

..

93

..

..

..

..

..

St. Lucia

..

16

35

57

..

93

..

71

..

14.0

..

St. Martin

..

..

..

..

..

..

..

..

..

..

..

St. Vincent and Grenadines

..

21

48

55

..

..

..

67

..

..

..

86d

730

55

0.4 d

..

87

54

..

..

.. ..

Sudan

31.7

Suriname

7.5

30

130

36

1.0

88

98

55

..

..

Swaziland

7.3

104

320

71

26.0

77

94

57

..

..

..

..

3

4

6

0.2

..

..

64

7

7.5

35

Sweden Switzerland

..

4

8

4

0.4

..

..

68

9

4.1

33

Syrian Arab Republic

10.1

15

70

38

..

106

95

43

33

8.4

9

Tajikistan

15.0

63

65

26

0.3

104

100

66

..

..

..

Economy

States and markets

Global links

Back

World Development Indicators 2013 41


2 People Prevalence Under-five of child mortality malnutrition, rate underweight

Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female mortality fertility of HIV completion literacy participation employment legislators, ratio rate rate rate rate senior Unpaid family officials, and workers and managers Modeled births per own-account

estimate 1,000 % of per 100,000 women ages population % of relevant live births 15–19 ages 15–49 age group

% ages 15–24

% ages 15 and older

workers % of total employment

% of total labor force

% of total

2005–11a

2011

2007–11 a

2007–11 a

2007–11 a

% of children under age 5

per 1,000 live births

2005–11 a

2011

2010

2011

2011

Tanzania

16.2

68

460

129

5.8

81b

77

89

..

..

..

Thailand

7.0

12

48

38

1.2

..

98

72

54

0.7